Journal of Intelligent & Fuzzy Systems - Volume 38, issue 1

Authors: Zhang, Xinsheng | Gao, Teng

Article Type: Research Article

Abstract: Aspect level sentiment classification task requires topical polarity classification for different description aspect. There is a polysemy in the same vocabulary, and the emotional polarity is different for different objects. Word embedding can capture semantic information but cannot adapt to the polysemy. Attention mechanism has achieved good performance in the above tasks; however, it is only able to get the degree of association between words and unable to get detailed descriptions. In this paper, the ELMOs model is used to adjust the polysemy of the word. The Transformer model is used to extract the features with the highest degree of …relevance to the target object for emotional polarity classification. Our work contribution is to overcome the polysemy interference, and use the attention mechanism to model the network relationship between words, so that the model can extract important classification features according to different target words. Experiments on laptop and restaurant datasets demonstrate that our approach achieves a new state-of-the-art performance on a few benchmarks. Show more

Keywords: Text sentiment classification, fine-grained sentiment analysis, attention mechanism

DOI: 10.3233/JIFS-179383

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 89-96, 2020

Authors: Wang, Zhongru | Ruan, Qiang

Article Type: Research Article

Abstract: Communication network security is an important part of the digital signal processor. In particular, the process bus replaces the traditional hard wiring, which makes the network system extend from the second to the first time, greatly increasing the network scale and network traffic; the information transmitted on the process bus is absolutely large. Most requirements require strict real-time and high reliability. Therefore, information security is a major problem that threatens the security, stability, economy, and quality operation of network systems, and needs to be paid enough attention. This paper introduces the methods of information classification and information merging to improve …the real-time information. It proposes to apply network security technologies such as information encryption technology, firewall technology, mobile agent, security management technology and virtual private network (VPN) technology to office network of the electric-power industry and analysed the specific application scenarios and effects. Show more

Keywords: Network video surveillance, embedded system, digital signal processor, network security subsystem

DOI: 10.3233/JIFS-179384

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 97-103, 2020

Authors: Zang, Jingfeng | Ren, Guibin | An, Yanlin | Piao, Yan

Article Type: Research Article

Abstract: Bad weather has a negative effect on the perceptual quality and degrades the performance of computer vision system. Therefore, a rain removal method based on dual-tree complex wavelet fusion is proposed. The algorithm can be further used for video surveillance system and intelligent transportation and other fields. The method analyzes from the perspective of frequency domain, using the dual-tree complex wavelet decomposition: decomposing images into low frequency sub-images and high frequency sub-images, then developing the different fusion rules. For the low frequency sub-images, fusion rules using the principal component analysis. For the high frequency sub-images, fusion rules using the local …energy matching. In this paper, an image edge enhancement algorithm based on fast guided filter is proposed, a SIFT feature matching method based on maximum likelihood estimation sampling and consistent(MLESAC) algorithm is proposed. Experiments results show that the proposed algorithm can improve the definition of images and restore the details of the target blocked by raindrops. Show more

Keywords: Raindrops removal, dual-tree complex wavelet fusion, PCA, local energy

DOI: 10.3233/JIFS-179385

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 105-113, 2020

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper designs a brand-new image retrieval method of mammary cancer based on convolution neural network. This method simulates VLAD layer in CNN network structure, designs a trainable universal VLAD layer-NET VLAD layer, reduces dimensions and optimizes VLAD descriptors, applies structure from motion algorithm to automatically label samples, and obtains the minimum loss function value by a new training program of weakly supervised ranking loss. Experiments show that this method has improved retrieval performance compared with similar retrieval methods and non-network structure retrieval methods.

Keywords: Convolutional neural network, VLAD, loss function, medical image retrieval

DOI: 10.3233/JIFS-179386

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 115-126, 2020

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper presents a medical brain image algorithm based on multi-feature fusion. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Then the heuristic search algorithm is used to optimize the feature selection stage. Based on the feature score table extracted …by the recursive feature elimination method of support vector machine, the correlation between features is added. Moreover, through experimental analysis, the optimal value of the parameter K was selected according to the heuristic search, and the optimal feature subset was extracted after determining the value of the parameter K. Experiments show that compared with similar algorithms, this algorithm improves the accuracy and efficiency of the classification of brain images. Show more

Keywords: Convolutional neural network, multi-feature fusion, heuristic search, medical image classification

DOI: 10.3233/IFS-179387

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 127-137, 2020

Authors: Zeng, Jun

Article Type: Research Article

Abstract: In order to improve the security of information storage in multi-domain optical network privacy protection, hybrid encoding and encryption of privacy protection information in multi-domain optical network is carried out. A hybrid coding and secure encryption technique based on particle swarm optimization (PSO) for privacy protection information in multi-domain optical network is proposed. The coding mapping equation of privacy protection information security encryption in multi-domain optical network is constructed, and the privacy protection information of multi-domain fiber network is loaded into the coding mapping equation of security encryption of privacy protection information in multi-domain fiber network. A set of characteristic …solutions describing the entropy function of the characteristic distribution of random encryption keys are obtained, and the elliptic mapping random linear combination coding and chaotic encryption key allocation are carried out. The privacy protection method of multi-domain optical fiber network is used to encrypt and decode information with mixed coding and steganography. Under the bilinear mapping coding system, the privacy-protected information in multi-domain optical network is encrypted and encrypted, stored and transmitted confidently. The simulation results show that this encryption technique has better steganography performance and better secure transmission and storage performance for the privacy protection information mixed encoding encryption in multi-domain optical network. Show more

Keywords: Particle swarm optimization algorithm, multi-domain fiber optic network, secure encryption

DOI: 10.3233/JIFS-179388

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 139-145, 2020

Authors: Chen, Limin | Li, Zhuohang | Lv, Muzhan | Xiong, Mingliang

Article Type: Research Article

Abstract: In order to improve the ability of automatic estimation and prediction of economic trend index, an intelligent prediction model of economic trend index based on rough set support vector machine is proposed. The statistical analysis of intelligent prediction of economic trend index is carried out by using the equivalent approximate linear model, and the regression analysis model of intelligent prediction of economic trend index is established. Combining with the rough set support vector machine big data fusion technology, the feature extraction and information mining are carried out in the process of intelligent prediction of economic trend index, and the statistical …time analysis series of economic trend index is constructed. The spatial distribution of economic trend index distribution series is reconstructed, and the economic trend is evaluated and predicted in the high dimensional economic trend index forecast series distribution space. The principal component characteristic analysis and fuzzy closeness analysis of economic trend index are carried out by using fuzzy relational degree scheduling method. Taking economic cost, economic development prospect and economic growth rate as constraint indexes, the method of multi-factor joint estimation is adopted. Realize economic trend index intelligent forecast. The simulation results show that the accuracy of fast estimation of economic trend index is high, the time cost is small, and the ability of intelligent prediction is stronger. Show more

Keywords: Rough set, support vector machine, economic trend index, intelligent prediction

DOI: 10.3233/JIFS-179389

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 147-153, 2020

Authors: Sun, Xiang

Article Type: Research Article

Abstract: With the continuous progress of network technology, some abnormal data are often confused in network data flow, which affects network security. In order to grasp the abnormal degree of abnormal data in networks and detect the similarity of abnormal data, an optimized genetic data mining algorithm is used to mine abnormal data in network, obtain the initial population of abnormal data mining and optimize genetic operation. On this basis, the network data type and the number of network data types are adaptively adjusted to obtain the optimal abnormal data mining results. Based on Euclidean distance, the similarity value of abnormal …data in network is calculated, and the greater the similarity value is, the greater the similarity of abnormal data is and vice versa. The experimental results show that the average standard deviation of detection error and energy consumption of the proposed method are 0.00865 and 398J, respectively. This method is a reliable and energy-saving method for similarity detection of abnormal data in network, which provides an effective basis for grasping the anomaly degree of network data. Show more

Keywords: Data mining, abnormal data in network, population, optimized genetics, similarity, detection

DOI: 10.3233/JIFS-179390

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 155-162, 2020

Authors: Li, Dakai | Zhang, Fan | Tian, Yuanli

Article Type: Research Article

Abstract: In the era of the Internet of Things, the way of information dissemination and the speed of information computing have changed dramatically. New generation technologies such as big data, IOTs, cloud computing, and mobile internet have rapidly developed, and the information resources in the process of using customers have promoted to value creation activities. The guiding force, therefore, the service model must also follow the changes. This paper is based on the enterprise management integration mechanism and information platform research of the Internet of Things environment, and analyses its conceptual model, the relationship between the platform and related subjects, the …value creation mechanism, the core business functions and the profit model, which have certain guiding significance for practice. The enterprise management integration mechanism and information platform research in the Internet of Things environment requires the parties to interact, share, and cooperate with each other to achieve common value creation. In addition, enterprises effectively research internal resource integration and information sharing, rationally streamline enterprise management institutions, thereby improving the quality and efficiency of business operations, giving full play to the role of internal control and risk management, so that enterprises can develop steadily. Show more

Keywords: Enterprise, information platform, internal control, Internet of Things, management integration

DOI: 10.3233/JIFS-179391

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 163-173, 2020

Authors: Xu, Tian | Fan, Jizhuang | Fang, Qianqian | Zhu, Yanhe | Zhao, Jie

Article Type: Research Article

Abstract: Collision detection is the core issue in physical human–robot interactions, and many detection methods based on robot dynamic models have been proposed. However, model uncertainties, especially complicated friction, seriously affect the collision detection performance of these methods. In this paper, a nonlinear disturbance observer (NDO) originally proposed for friction estimation is applied for the first time in robot collision detection. To verify that the collision detection performance of the NDO is better than that of the classical generalized momentum observer (GMO), the detection sensitivity, robustness and external torque estimation accuracy of each method are compared and analyzed. Then, to eliminate …the effects of friction uncertainties on the collision detection results, a modified nonlinear disturbance observer (MNDO) based on neural networks is proposed to improve the collision detection performance. To verify the effectiveness of the algorithm, simulations and experiments are conducted with a 6-DOF robot and two single-joint platforms. The results indicate that the proposed algorithm is accurate and effective. Show more

Keywords: Robot collision detection, NDO, GMO, friction estimation, neural networks

DOI: 10.3233/JIFS-179392

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 175-186, 2020

Authors: Song, Depeng | Li, Binbing | Qu, Yi | Chen, Yijun

Article Type: Research Article

Abstract: The frequency modulated continuous wave circular synthetic aperture radar (FMCW CSAR) is a high resolution imaging radar, which plays an important role in target recognition. However, the traditional wave number domain imaging algorithm has a low resolution for the target far from the scene center, which limits its wide applications in CSAR imaging. In this paper, when the targets are sparse or compressible, a circular convolution algorithm based on compressed sensing is proposed to improve the resolution. In the algorithm, the circular convolution and the Fourier transform is used to reduce computation cost. What’s more, the compressed sensing is applied …to improve the imaging resolution for the target far from the scene center, which can effectively avoid the complex calculation of the system kernel function in the traditional wave number domain algorithm. Some simulation results illustrate the effectiveness of the proposed method. Show more

Keywords: FMCW CSAR, compressed sensing, circular convolution, imaging

DOI: 10.3233/JIFS-179393

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 187-196, 2020

Authors: Wu, Peng | Li, Wei | Yan, Ming

Article Type: Research Article

Abstract: The traditional point cloud alignment method suffers from drawbacks such as a large extensive computation, low computing speed, and poor alignment accuracy. To overcome these problems, this paper proposes a fast and highly accurate algorithm based on fast point feature histograms (FPFH) algorithm and spatial constraints. The proposed algorithm first filters, denoises the point cloud dataset, and calculates the point cloud normal to obtain the FPFH eigenvalue. Then, the vertebral space is divided into three regions according to its location, and the feature points in each region are calculated. The Euclidean distance between a feature point and the boundary of …the adjacent region, and the weight coefficient corresponding to the feature point are given according to the calculated distance. The method overcomes the defect that the query feature point has a large workload in the traditional ICP algorithm and improves the registration precision of the point cloud. The experimental results show that the proposed method effectively solves the problems of the traditional point cloud registration algorithm, can effectively reduce the mismatch rate of point cloud registration, and can improve the registration accuracy and stability without reducing the registration of the elements. Show more

Keywords: Point cloud alignment, FPFH, ICP

DOI: 10.3233/JIFS-179394

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 197-206, 2020

Authors: Wu, Ling | Hu, Hao | Zhao, Weihua | Liu, Haoxue | Zhu, Tong

Article Type: Research Article

Abstract: Previous studies lack a comprehensive evaluation model that combined the subjective perception of the driver and the objective driving environment. This work investigates the characteristics of drivers’ behavior risk in highway extra-long tunnels. Real-vehicle tests were conducted in two typical extra-long tunnels and the speed of skilled and unskilled drivers were collected simultaneously. The quantified model of drivers’ behavior risk was proposed based on the safety speed difference. The variation characteristics of behavior risk both inside the tunnel and ordinary highway were analysed. Further, the NARX neural network was used to predict real-time speed with the heart rate regarded as …the input variable. Results showed that skilled drivers showed the highest behavior risk in the internal zone, while the highest value of unskilled drivers was at the exit zone in the tunnel section. Both two types of drivers presented the highest and the lowest behavior risk on the ordinary highway and the tunnel entrance zone respectively. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern the driver’s risk characteristics in Internet of Vehicles and how to establish the automated driver model in the simulation driving environment. Show more

Keywords: Time-series modelling, NARX neural network, driver, behavior risk characteristics, safety speed difference

DOI: 10.3233/JIFS-179395

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 207-217, 2020

Authors: Liu, Yan-Xiao | Yang, Ching-Nung | Sun, Qin-Dong | Chen, Yi-Cheng

Article Type: Research Article

Abstract: Traditional (k , n ) secret image sharing provides all-or-nothing decoding model and (k , n ) scalable secret image sharing provides progress decoding model during image reconstruction. Both these two decoding models are significance in various applications. However, the security level for real applications would change due to the dynamical environment, only one single decoding model cannot satisfy the changeable security requirement. In this work, we construct scalable secret image sharing schemes that provides both all-or-nothing and progress decoding models to satisfy the dynamical secure requirement. Each participant in our schemes only needs to keep one initial-shadow. During image …reconstruction, the dealer selects the decoding model according to current security requirement, if progress model is chosen, initial shadows can achieve image reconstruction in progress model without any modification; else if all-or-nothing model is chosen, the dealer does not need to resent new shadows to participants, the initial-shadows can be updated to satisfy all-or-nothing model efficiently. Show more

Keywords: Secret image sharing, scalable, decoding model, all-or-nothing, progress

DOI: 10.3233/JIFS-179396

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 219-228, 2020

Authors: Li, Zhao | Song, Yi | Gong, Guoqiang | Zhou, Siwei | Lv, Ke

Article Type: Research Article

Abstract: Fault localization is the critical but most expensive step in testing manufacturing software, effectively locating faults has become an increasingly concerned study. The existing spectrum-based fault localization techniques utilize spectrum information and specific prioritization algorithm to generate the suspiciousness as well as the ranking of statements. However, the effectiveness of fault localization in manufacturing software would be dramatically reduced once the statement involving bug is assigned with the same suspiciousness as other non-faulty statements. A multi-technique fusion approach (FA) is proposed based on suspicious rankings, which merges various of randomly selected fault localization techniques to minimize the difference between the …numbers of statements that need to be examined (GAP) to find the bug respectively in the worst and best assumptions, further improve the effectiveness of fault localization. In addition, a novel metric for comparing fault localization techniques is developed. Experiments on Siemens Suite shows that our approach outperforms these selected techniques in the effectiveness. Show more

Keywords: Fault localization, manufacturing software, spectrum information, multi-technique fusion, GAP

DOI: 10.3233/JIFS-179397

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 229-238, 2020

Authors: Sun, Yang | Li, Jianrong | Fu, Xueliang | Wang, Haifang | Li, Honghui

Article Type: Research Article

Abstract: Task scheduling in the cloud environment is a hot issue in current research. Aiming at the task scheduling problem in cloud environment, this paper analyses the scheduling model of cloud tasks, proposed an improved genetic algorithm (PGA) based on phagocytosis, changed the crossover operation of standard genetic algorithm (GA), formed a sub-chromosome individual after phagocytosis of two mother chromosomes, another individual was generated randomly, and the new individual generated after phagocytosis is determined by the fitness function and the load-balancing standard deviation, so that the evolution process can ensure a high proportion of high-quality individuals in the population. Ensure the …diversity of the population. Then a multi-population hybrid coevolutionary genetic algorithm (MPHC_GA) is adopted, which uses the Min-Min algorithm to generate initial multiple sub-populations, and these sub-populations are evolved by standard genetic algorithm (GA) and improved genetic algorithm (PGA) based on phagocytosis. The simulation results show that the proposed algorithm is effective in cloud task scheduling. Show more

Keywords: Task scheduling, genetic algorithm, phagocytosis, multi-population hybrid coevolutionary

DOI: 10.3233/JIFS-179398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 239-246, 2020

Authors: Li, Honghui | Lu, Hailiang | Fu, Xueliang

Article Type: Research Article

Abstract: With the rapid development of data center network, the traditional traffic scheduling method can easily cause problems such as link congestion and load imbalance. Therefore, this paper proposes a novel dynamic flow scheduling algorithm GA-ACO (Genetic Algorithm and Ant COlony algorithms). GA-ACO algorithm obtains the global perspective of the network under the SDN (Software defined network) architecture. It then calculates the global optimal path for the elephant flow on the congestion link, and reroutes it. Extensive experiments have been executed to evaluate the performance of the proposed GA-ACO algorithm. The simulation results show that, in comparison with ECMP and ACO-SDN …algorithm, GA-ACO can not only reduce the maximum link utilization, but also improve the bandwidth effectively. Show more

Keywords: Data center network, SDN, elephant flow scheduling, genetic algorithm, ant colony algorithm

DOI: 10.3233/JIFS-179399

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 247-255, 2020

Authors: Lei, Guoping | Luo, Xiuying | Cai, Li | Gao, Le | Dai, Nina | Xu, Qingshan | Tan, Zefu

Article Type: Research Article

Abstract: Battery management system (BMS) is an important part of electric vehicle that can improve the efficiency of battery and ensure the safety during operating process. State of charge (SOC) estimation is one of kernel technology of BMS. High precision of SOC estimation can not only increase service life of battery, but also enhance energy utilization efficiency and cut down the operational cost. Based on fully understand working principle of battery, three-order RC equivalent circuit is chose to simulate the external characteristics. Introduce the working theory of that combination of extended Kalman filter (EKF) and open circuit voltage (OCV), and the …whole recursive algorithm of estimation SOC, using the OCV-SOC look-up table to solve the problem of initial value of SOC to a certain degree. The hardware circuit and software of BMS are designed. Hardware circuit consists of current measurement circuit, voltage measurement circuit, temperature measurement circuit and equalization circuit. The software is designed by C as the development language, the Microsoft Visual Studio 2008 as development environment and SQL Server 2008 as database management system. The experiments are carried out after the experimental platform of system hardware and software is constructed. The system realizes the real-time online monitoring of BMS, SOC estimation and etc. The result verifies the reliability and feasibility. The precision requirement of SOC estimation by using EKF algorithm and OCV-SOC look-up table meets the national standard for electric vehicle. Show more

Keywords: Electric vehicle, battery management system, smart EFK algorithm, extended kalman filter, state of charge

DOI: 10.3233/JIFS-179400

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 257-262, 2020

Authors: Bian, Qian | Zhang, Xuejun | Wang, Zhenduo | Liu, Mujun | Li, Bijiang | Wu, Dongbo | Liu, Gang

Article Type: Research Article

Abstract: Multi-phase computed tomography images are widely applied to doctors’ routine interpretation of organic lesions or before human abdominal surgery. However, because of the lack of intuitive and three-dimensional (3D) observations, human factors lead to 80% of the clinical errors. A primary malignant tumor resection system based on a virtual reality (VR) helmet and a force-feedback device combined with a 3D printing model is proposed in this paper. First, we used the thin-plate spline (TPS) deformation method to register the different phase images. In the case of a metastatic tumor, a spherical scoring filter (SSF) model was built for searching the …tumor pattern with edge detection and subtraction processing, from which the initial tumors were selected on the basis of the calculated score. For hepatocellular carcinoma cases, candidates were extracted as the areas without edges by using edge detection filters on the subtraction image between the equilibrium and arterial phase images. Finally, the false positive (FP) candidate was eliminated before obtaining the 3D shape of the liver tumor in the expansion process, thus providing an accurate volume of lesions for the surgical plan for the liver resection. The results showed that our virtual surgery system enabled the user to simulate the use of a scalpel for cutting and removing the organ labels; 3D display on a VR helmet with a deformable effect; and touching organs with a force-feedback device. Our virtual surgery tools could simulate all of the effects of the doctors’ operations and make clinical practice more efficient. Show more

Keywords: Virtual surgery system, hepatocellular carcinoma (HCC), metastatic tumor, multi-detector CT (MDCT), spherical scoring filter, force-feedback device

DOI: 10.3233/JIFS-179401

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 263-276, 2020

Authors: Zeng, Zhijun | Gao, Yong | Liu, Liyan | Yan, Xiaojun | Xu, Guoliang | Liu, Hongning | Ji, Yanhua

Article Type: Research Article

Abstract: Although it is very important to pay attention to the personalized medicine of tumour patients, there is quite lacking some methods to evaluate the synergistic effects of the top anti-cancer drugs in clinic. In the study, therefore, we used the network of pharmacogenetic and bioinformatics to discuss the complex interactions in the top anti-cancer drugs with the help of computer high performance operating power and network visualization. We got a total of 81 known targets from the top 10 anti-cancer drugs. The shared most targets were from the 5-fluorouracil, capecitabine and tegafur, occupying 4, 4 and 3 targets, respectively. Based …on complex network visual effect of the computer, gene set enrichment analysis displayed that the targets were mainly on five major categories. All the data showed that the two groups of drugs having some synergistic effects (5-fluorouracil, capecitabine, tegafur and tamoxifen, letrozole, respectively), which is suggests the top anti-cancer drugs’ synergic existing in combination drugs on clinic. Show more

Keywords: Computer, visualization, pharmacogenetics, caner, anti-cancer drugs

DOI: 10.3233/JIFS-179402

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 277-281, 2020

Authors: Lu, Yujun | Hu, Xiaoyong | Su, Yu

Article Type: Research Article

Abstract: According to the large amount of and diversity of current industrial manufacturing data, on the basis of analyzed limitations of current industrial networking sensing system, a framework of industrial networking sensing system based on edge computing and artificial intelligence is put forward, including data-getting sensors group, first-level sensor routers, second-level sensor routers and backend severs. The above framework mainly is studied from three perspectives: structure level, workflow and key technologies, and the technology of artificial intelligence is the key to achieve this system with analysis of involved computational intelligence technology, information fusion technology and decision technology. This framework of industrial …networking sensing system has important reference value on improving timeliness and certainty of industrial networking communications, largely reduces the entire power consumption and reduce stress of background sever. Show more

Keywords: Industrial networking, perceptual layer, edge computing, artificial intelligence

DOI: 10.3233/JIFS-179403

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 283-291, 2020

Authors: Ding, Man | Bai, Zhonghang | Zhang, Jinzhu | Huang, Xiaoguang

Article Type: Research Article

Abstract: A dynamic color design model and method are proposed for a class of industrial product color design problems with dynamic changes in the appearance of products and different appearance in different operating modes. These types of industrial products that have a variety of operating modes in the operating cycle are defined as multimodal industrial products (MMIPs). For a single mode, a single-modal industrial product (SMIP) color design model is established by using users’ color image requirements as the design goal to transform the dynamic color design problem of products into weighting forms of several single modes and to realize the …discretization of continuous problems. Finally, a dynamic color design model of MMIPs is established. A genetic algorithm (GA) is used to optimize this model to obtain the color design scheme that conforms to the users’ dynamic image perception. Finally, by means of an example of color design about engineering machinery, this method is demonstrated to be feasible and applicable for dynamic color design optimization of MMIPs. Show more

Keywords: Genetic algorithm (GA), image, dynamic optimization, color design, multimodal industrial product (MMIP)

DOI: 10.3233/JIFS-179404

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 293-302, 2020

Authors: Xiao-Lan, Liu | Gui-Zhen, Lu | Jun-Liang, Zhang

Article Type: Research Article

Abstract: Theory of Characteristic Mode(TCM) has become a research hotspot in antenna design. The development of computational electromagnetic makes it possible to solve the eigenmode of microstrip antenna with arbitrary shape. In this paper, TCM with radiation boundary conditions is proposed to solve the input impedance of the antenna, and TCM based on differential equations is applied to the design of the circular wide-band wearable antenna with polygonal slot. By analyzing the radiation characteristics of different modes of the antenna, the optimal feeding place is selected to excite the desired mode by the normalized electric field distribution of different modes, and …then the wide-band characteristics are obtained. Experiments show that the circular wide-band wearable antenna with polygonal slot presented in this paper has good performance with bandwidth enough to covers (5.725GHz–5.85 GHz) frequency band and certain flexural resistance from a certain angle for wearable intelligent equipment applications. Show more

Keywords: Wearable antenna, TCM, feeding place, wide-band

DOI: 10.3233/JIFS-179405

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 303-309, 2020

Authors: Xiong, Junhua | Li, Ruisheng | Wang, Tingling | Gao, Jinfeng

Article Type: Research Article

Abstract: To solve the problem of harmonic distortion generated by the output AC of inverters without considering the relationship between carrier switching frequency and carrier frequency, by analyzing the influence of carrier switching frequency on random carrier signal, it was concluded that the phase mismatch between the front and back carriers was the fundamental reason for the distortion of the output voltage of inverters when the preset carrier was switched randomly. And the switching frequency was randomized by switching the preset carrier, i.e., an improved kind of random carrier frequency modulation (RCFM). The simulation and experimental results showed that the proposed …random PWM method could not only suppress the high-order harmonics of the output voltage more effectively, but also have better sinusoidal waveform than the conventional random PWM method. Show more

Keywords: Switching frequency, random PWM, harmonic suppression, preset carrier

DOI: 10.3233/JIFS-179406

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 311-318, 2020

Authors: Li, Xiaomian | Shu, Yufeng | Zuo, Dali | Zhang, Junhua | Chen, Zhanshuo | Gan, Haoxian | Li, Junlong | Li, Juntao | Chen, Kaiwen | Yang, Guohui

Article Type: Research Article

Abstract:  In today’s globalized economy, various industries are promoting product transformation and upgrading. The textile industry is also facing a harsh international situation and fierce market competition. While constantly promoting the upgrade of automation equipment, the original quality control mode relying on manual testing has been unable to meet the modern production requirements and the market demand for product quality. This paper investigates the product inspection and quality control in the textile industry at home and abroad, and puts forward the application of machine vision technology in textile automated inspection and quality control, so As to strengthen the product quality control …system and improve the product’s physical quality. By studying the composition of machine vision detection technology, this paper studies the two core technologies of image acquisition and image processing in machine vision, summarizes and analyzes the common defects of textile Products, and proves that the common defects can be detected and repaired in time by machine vision detection method. Show more

Keywords: Machine vision, defect, automatic detection, image processing, textiles

DOI: 10.3233/JIFS-179407

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 319-325, 2020

Authors: Du, Zhiqiang | Cui, Shigang

Article Type: Research Article

Abstract: In wind farms with high integrated automation systems, different communicated structures, such as different communication protocols and communication mediums, exist among various intelligent equipment. Different communication protocols or media will lead to incompatibility of communication between various intelligent devices. Developing communication protocol converters is an effective way to solve such problems. In this way, the communication efficiency between intelligent devices will be affected to some extent, and then the operation of the whole wind farm will be affected. This study introduces a communication protocol converter integrated with a multiserial, multiprotocol, and multinetwork system. The protocol converter treats the microcontroller STM32F407 …as the microcontroller unit of the converter to integrate multiple communication interfaces. Meanwhile, the compatibility problems of communication between the intelligent equipments in the wind field monitoring system can be solved using software to realize the conversion between the various communication protocols. Show more

Keywords: Wind farm, monitoring system, communication protocol converter, protocol conversion

DOI: 10.3233/JIFS-179408

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 327-335, 2020

Authors: Sun, Changxia | Liu, Yi | Zeng, Xia | Si, Haiping

Article Type: Research Article

Abstract: Provable security theory generally adopts the method of reduction, which makes use of the unsolvable mathematical problems in number theory to reduce the scheme to be safe. The idea of proof is a method of proof by contradiction: First, it is assumed that it is not difficult to solve the scheme presented in this paper, then the process of proving it, and finally, it is deduced that it is not difficult to calculate a certain difficult problem, which contradicts the difficulty of the mathematical problem. Then, it means that the assumption is not valid, and the scheme is proved to …be safe. In this paper, the security of the scheme proposed in our previous paper is proved in detail.the scheme is proved to be secure against existential forgery under selective attributes and adaptive chosen-message attack. Its security can be reduced to the hardness of the computational Diffie-Hellman problem. Show more

Keywords: Proxy signature, attribute-based, original signer, proxy signer, provable security, CDH problem

DOI: 10.3233/JIFS-179409

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 337-343, 2020

Authors: Ren, Xiaoling | Wang, Wen | Xu, Shijun

Article Type: Research Article

Abstract: It is the key step of the classification and recognition to segment 3D point cloud. Aiming at the shortcomings of super-voxels concavo-convex segmentation algorithm for 3D point cloud, an efficient segmentation method based on multi-feature fusion is proposed. Firstly, the noises of 3D point cloud are removed by the statistical outlier removal filter, and the denoised 3D point cloud is simplified by the voxel grid filter. Secondly, it is divided into many voxels with the same size by the octree, and the voxels with the smallest mean curvature in local neighbourhood are used as seed voxels for regional growth to …form super-voxels. Next, the super-voxels adjacency graph is structured and the concave-convex feature, continuous feature and colour feature between adjacent super-voxels are calculated as the weight on their edges. Finally, an arbitrary super-voxel is selected as the seed super-voxel to regional growth based on multi-feature weights of the edges in order to achieve the segmentation of the point cloud. The experimental results show that the proposed method whose segmentation speed, stability and accuracy are higher than existing methods greatly improves the over-segmentation or under-segmentation of the super-voxels segmentation algorithm. Show more

Keywords: Image processing, concave-convex segmentation, 3D point cloud, multi-feature fusion, region growth, colour feature

DOI: 10.3233/JIFS-179410

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 345-353, 2020

Authors: Xiong, Junhua | Li, Ruisheng | Wang, Tingling | Gao, Jinfeng

Article Type: Research Article

Abstract: Aiming at the optimization of power source capacity in multi-energy industrial parks, an economic optimization model with the lowest comprehensive cost of the system as the objective function was established, and an improved particle swarm optimization algorithm with natural selection strategy and chaos theory was proposed to optimize the model. This algorithm initialized particle fitness by chaotic mapping, added natural selection strategy to the iterative optimization process, and used chaotic ergodicity to search solution space. The test function simulation showed that the algorithm had the characteristics of fast convergence, high precision and being not easy to fall into local optimum. …A case study of a certain area in Hebei Province, China, was selected to analyze the example, and the power source capacity optimization design scheme was obtained. The analysis results verified the effectiveness of the algorithm. Show more

Keywords: Particle swarm optimization (PSO), natural selection, chaos, industrial park, capacity planning

DOI: 10.3233/JIFS-179411

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 355-363, 2020

Authors: Zhang, Shuo | Zhao, Xuan | Lei, Wubin | Yu, Qiang | Wang, Yibo

Article Type: Research Article

Abstract: On account of the limitations of single sensor in obstacle detection, the paper investigates an obstacle detection method based on the fusion of 3D LiDAR and monocular visual. The spatial data fusion of the two sensors is realized according to their calibration results, and the time data fusion is realized by using double buffer technology. Considering the aspect ratio of vehicles, the image region of interest is determined based on the obstacle clustering of 3D LiDAR data. By using Haar-like features as effective characteristic of the front vehicle, integral figure is applied to extract Haar-like features of vehicle samples and …non-vehicle samples. AdaBoost algorithm is used to choose weak classifiers to constitute strong classifiers, which combine into the cascade classifier. The cascade classifier has been trained to identify the vehicle target in the image region of interest. The relevant experimental results verify the effectiveness and real-time performance of the detection method. Show more

Keywords: Obstacle detection, multi-sensor fusion, vehicle identification, AdaBoost algorithm

DOI: 10.3233/JIFS-179412

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 365-377, 2020

Authors: Deng, Leilei | Wang, Zhenghao | Wang, Chuang | He, Yifan | Huang, Tao | Dong, Yue | Zhang, Xian

Article Type: Research Article

Abstract: Image segmentation technology is a basic technology for image processing and analysis. As a typical interactive color image segmentation algorithm, grabbing segmentation has high precision, interactive operation and better segmentation effect in processing complex background segmentation, and has broad prospects in the field of agriculture. In this paper, the image segmentation algorithm of maize smut, Maize Head Smut and maize rust, which are three main diseases and insect pests, is studied by taking the high-yield crop Maize in Northeast China as an example. The image background in the static image editing is replaced by an improved one-time cutting algorithm. Through …the adaptive combination of weights, the depth information and saliency information are combined into the grabbing color model. The improved image segmentation algorithm greatly improves the efficiency and accuracy of image segmentation, and achieves a good spot segmentation effect in the static image of corn pests and diseases, and has a high recognition. Do not rate. And it plays a predictive research effect in practical verification. Show more

Keywords: Threshold segmentation, graph segmentation, grab cut algorithm, saliency, maize diseases and pests

DOI: 10.3233/JIFS-179413

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 379-389, 2020

Authors: Fei, Rong | Li, Shasha | Hei, Xinhong | Xu, Qingzheng | Zhao, Jiayu | Guo, Yuling

Article Type: Research Article

Abstract: Using the Semi-Markov decision model, we start with the real road map datum with a constructed logic network and construct the complex road network with random moving characteristics. First we translate the crowdsoured map datum into the vectorgraph in road network by the ArcGIS with the conversion of longitudinal and Latitude Coordinates to planar coordinates. In the motion simulation model all objects are sorted by the time of state change, and the moving object with the closest state change time to the current time are set at the front of the queue. And then, the moving object motion model based …crowdsourced map datum is simulated. The experimental results for fitting and analysing the distribution rules of in-degree and out-degree show that the designed model can satisfy the Poission Distribution Rule on the cross node of Road Network based Uniform Distribution of moving object random motion, which conform to the characteristics of Distance Space and small-world network. Show more

Keywords: Semi-markov model, real road map, moving object, distribution rule, motion simulation model

DOI: 10.3233/JIFS-179414

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 391-407, 2020

Authors: Hu, Yun | Zhou, Zuojian | Hu, Kongfa | Li, Hui

Article Type: Research Article

Abstract: Detecting community structure is critical in analysing social networks which are flourishing and influencing every aspect of people’s social life. Most social network systems are composed with complicated entity relations such and social interests, user relationships and their interactions. To understand how users interact with each other under the community level, its not enough to consider one kind of these relations while ignore the other. An united network model that can comprehensively integrate these relations is essential for community detection. Focusing on such kind of problem when dealing with social network with multiple relations, this paper proposes a heterogeneous network …model which characterizes and constructs user similarity relations by combining both of users’ interests and their interactions attributes. Based on the heterogeneous similarity model, an additive spectral decomposition algorithm is applied to detect overlapped communities from the network. The remarkable effect of our heterogeneous model is the ability to reveal most important attributes of the blog network. And, comparing to crisp clustering method, the additive spectral decomposition algorithm proposed is effective for finding overlapped user groups which is more reasonable among social networks where users tend to join multiple social groups. Results of experimental studies on real-world and synthetic datasets demonstrate the effectiveness of the algorithm with respect to the size, the distributive structure and the high dimensionality of the datasets. Show more

Keywords: Community detection, micro blog network, user interest, user interaction, heterogeneous network model, user similarity modelling

DOI: 10.3233/JIFS-179415

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 409-416, 2020

Authors: Wang, Yuanyuan | Wang, Zhijian | Jiang, Mingxin | Chen, Liqi | Shen, Tianhao | Zhang, Wenyang

Article Type: Research Article

Abstract: Person re-identification (ReID) is a critical work in the field of intelligent image processing and deep learning, which has attracted the attention of industry application. Person ReID focuses on matching person images obtained from non-overlapping camera views and finding the person-of-interest. An important unresolved problem is to obtain efficient metric for measuring the similarity among pedestrian images. Lately, deep learning with metric learning has become a general method for person ReID. Yet, previous methods mainly used a variety of distance to measure the similarity among samples. The way of distance measure is more sensitive when the scale changes. In this …paper, we propose angular loss with hard sample mining (ALHSM) to learn better similarity metric for the person ReID. Our work uses the angular relationship in triangles as a measure of similarity, minimizing the angle at the negative point of the triangle. ALHSM combines with hard negative mining strategies, which learn better similarity metric and achieve advanced performance on several benchmark datasets. The experimental results show that our work is competitive compared to the state-of-the-art. Show more

Keywords: Person re-identification, deep learning, angular loss, intelligent image processing

DOI: 10.3233/JIFS-179416

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 417-426, 2020

Authors: Wei, Dongping | Tang, Niansheng | lei, Tianli | Wen, Shouwen

Article Type: Research Article

Abstract:  Language Model is used to describe and calculate the probability of a reasonable sentence occurrence in natural language. In practical applications, language model as the core of natural language processing is often used in machine translation, information indexing, voice recognition, context processing such as sentiment recognition and other tasks. We will discuss advantages and weaknesses of traditional statistical language models and neural Network Language Models such as CBOW and Skip-gram. Keeping in view the traditional statistical language model and neural network model, we will try to put forward the word vector model based on part of speech and sentiment information …(PSWV-model) in order to use more natural language information such as word order features, part of speech features, and sentiment polarity information under the framework of Mikolov’s model. And finally we will present our deliberations on some advantages of PSWV model and other models including CBOW and Skip-Gram, CDNV in the NLP tasks including named entities recognition and sentiment polarity analysis. Show more

Keywords: Deep learning, word vector, sentiment analysis, named entity recognition

DOI: 10.3233/JIFS-179417

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 427-440, 2020

Authors: Han, Hongmu | Dong, Xinhua | Zuo, Cuihua

Article Type: Research Article

Abstract: Recommender systems are widely used to provide users with items they may be interested in without explicitly searching. However, they suffer from low accuracy and scalability problems. Although existing clustering techniques have been incorporated to solve these inherent problems, most of them fail to achieve further improvement in recommendation accuracy because of ignoring the correlations between items and the different effects of item attributes on recommendation results. In this article, we propose a novel recommendation algorithm to alleviate these issues to a large extent. First of all, users and items are clustered into multiple cluster subsets based on user-item rating …matrix and item attribute deriving from domain experts, respectively. Then we use a selection method relying on item attribute to mine candidate items and only their predictions will be calculated in the next step, which can save the computation time greatly. Furthermore, by weighting the predictions with TF-IDF (Term Frequency-Inverse Document Frequency) weights, the top-N recommendations are generated to the target user for return. Finally, comparative experiments on two real datasets demonstrate that this algorithm provides superior recommendation accuracy in terms of MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). Show more

Keywords: Recommender systems, clustering, item attribute, weight, recommendation accuracy

DOI: 10.3233/JIFS-179418

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 441-451, 2020

Authors: Wang, Sheng | Yu, Yongchang | Yang, Chen | Liu, Long | Zhang, Yahui | Zhang, Zhi | Li, He

Article Type: Research Article

Abstract: Traditional soybean seeders are driven by land wheels, which are easy to slip in complex operating conditions, resulting in the increased miss-seeding index and row-spacing coefficient of variation, etc. In order to solve these problems, a soybean electrical-control seeding system was designed in this paper. For improving the control accuracy of the electrical seeding system and achieving precise control of soybean seeding, the closed-loop control was adopted in the electric-driven Soybean Seeding system, the motor model of the electric-driven soybean seeding system was established and the transfer function of the motor was obtained. The PID control parameters were obtained by …the Ziegler-Nichols PID tuning method, and the corresponding parameters were substituted into the control system simulation model established in MATLAB/SIMULINK. The conventional PID control system and the fuzzy PID control system were simulated respectively. Field trial results show that seeding with fuzzy PID control is better. Show more

Keywords: Seed metering device, electronic control, fuzzy control

DOI: 10.3233/JIFS-179419

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 453-462, 2020

Authors: Zhang, Xian | Wang, Fengxian | Han, Dawen | Meng, Hao | Wei, Bin | Wang, Songcen | Li, Yang | Xue, Ming | Yang, Qingxin

Article Type: Research Article

Abstract: Wireless power transmission technology avoids the problem of towed wires in the process of using electric energy, and increases the flexibility of using electricity. It is a hot research topic at present. In order to improve the system performance, a field-circuit coupling algorithm is proposed to analyze the system performance, with the help of the concept of supercomputing. Frequency splitting is a phenomenon in wireless power transfer (WPT) system when the coupling distance is less than the splitting point, the load power changes from a single-peak curve to a double-peak curve driven by two non-intrinsic resonant frequencies. Asymptotic coupled mode …theory (CMT) method is used to analyse the frequency splitting phenomena in WPT system. It provides detailed information about interaction of field strength under different coupling states through coupled solution of FEM and CMT. Over coupling, critical coupling and under coupling are three typical states classified by frequency splitting. Experimental results are acquired by two helical resonators. The overall system reaches the critical coupling state when resonators space 1.5 m and the total power on the load is 110 W. Therefore, it is an efficient way to forecast transmission characteristics by using this method. Show more

Keywords: magnetic resonant coupling, frequency splitting, coupled mode theory, critical coupling, coupled solution

DOI: 10.3233/JIFS-179420

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 463-469, 2020

Authors: Wang, Yajun | Sun, Fuming | Li, Xiaohui

Article Type: Research Article

Abstract:  To reduce and eliminate the three problems for large-scale data sets that include high computational complexity, large storage space, and long time-consuming in complex batch process with inherent dynamics and nonlinearity, a novel approach based on multi-dynamic kernel principal component analysis (MDKPCA) by exploiting compound dimensionality reduction for fault detection is proposed. The method firstly uses discrete cosine transform (DCT) having strong energy aggregation and distance preserving property to realize dimensionality reduction without changing the essential characteristics of data. Then after the reduced dimension data is processed by inverse transformation, the dynamic kernel principal component analysis (DKPCA) model is established …by combining the autoregressive moving average time series (ARMAX) model and kernel principal component analysis (KPCA) to handle the nonlinearity and dynamics in industrial process. Finally, one penicillin fermentation process case for fault monitoring is provided to test the effectiveness of the proposed method, where the comparison with multiway kernel principal component analysis (MKPCA) results is covered. Show more

Keywords: Compound dimensionality reduction, discrete cosine transform, multi-dynamic kernel principal component analysis, large-scale data set, penicillin fermentation process

DOI: 10.3233/JIFS-179421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 471-480, 2020

Authors: Wang, Yang | Zhang, Shengyu | Cen, Hongjie | Zou, Bo

Article Type: Research Article

Abstract:  The explosive growth of wireless data services, especially more and more requirement for high-definition videos, demands higher capacity of future wireless communication systems to meet this trend. One efficient solution to this problem is to improve the spectral efficiency. This paper analyzes the basic principles of large-scale antenna array system, whose performance is verified by simulation. Key technologies on large-scale antenna array system, such as channel state information acquisition, antenna array design, code book design, are also studied. The results show that large-scale antenna array system can greatly improve spectral efficiency and reduce system energy consumption.

Keywords: Large-scale antenna array system, massive MIMO, spectral efficiency, interference mitigation

DOI: 10.3233/JIFS-179422

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 481-486, 2020

Authors: Wu, Shaofei

Article Type: Research Article

Abstract: We propose models based on SVM, Naïve Bayes and deep learning to solve the consumption intention classification problem. Applying consumption intention mining to prediction tasks in social media. This paper discusses consumption intention towards a certain kind of product, i.e. movie, and uses movie consumption intention as an important feature in box office prediction. We combine consumption intention with traditional features used in the problem of box office prediction, and achieve a outperforms previous work of this problem We build a system based on linear regression which automatically predicts movies’ total box office and opening weekend box office one day …prior to the movie’s release date. Show more

Keywords: Text intention mining, SVM, deep learning

DOI: 10.3233/JIFS-179423

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 487-494, 2020

Authors: Liu, Hui | Li, Yifan | Hong, Rui | Li, Zhenming | Li, Ming | Pan, Wei | Glowacz, Adam | He, Hao

Article Type: Research Article

Abstract: In order to trace the research trends and hotspots related to the field of driver behavior research both in China and worldwide, a bibliometric analysis was performed to systematically analyze 7208 scientific papers about driver behavior in the Web of Science database from 1957 to 2018, and the results were discussed from the 6 perspectives of growth trends of publications, geographical distribution, subject categories, institutions, authors and keywords distribution. The results show that research on driver behavior has been increasing rapidly since the 1990 s, but research in Europe and the United States started more than 20 years earlier than in …China. Currently, transportation, engineering, computer science and behavioral science have replaced the traditional subject categories, becoming the most important domains in this field. Research on driver behavior focuses on safety and systems using simulation models which is interacted with almost everything concerning traffic operation and safety. The current trend is that more researchers are working on understand the driver-vehicle-system interactions under the environment of connected and autonomous vehicle. Further research is needed to focus on unsafe driving behavior based on driver-vehicle-system interactions. This study will provide scholars in related academia and industry with panoramic knowledge of driver behavior research, as well as research hotspots and future research directions. Show more

Keywords: Driver behavior, research trends, driving safety, knowledge graph, visualization

DOI: 10.3233/JIFS-179424

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 495-511, 2020

Authors: Huang, Jun | Zhuo, Yumin | Tian, Xuemei | Zhu, Dingju | Mustafa, Rashed

Article Type: Research Article

Abstract: Conventional methods for disease treatment plan rely too much on the subjective experience and theoretical knowledge of doctors The uncertain decisions of doctors may lead to wrong treatment plans. This paper provides a treatment suggestion system based on big data and knowledge base. The system no longer relies on the subjective experience of doctors, but relies on the objective historical data of treatment cases including disease information, personal information, treatment plans and the treatment effects of the treatment plans. The suggested treatment plans are much more targeted and reliable, thereby assisting doctors to determine disease treatment plans more quickly, accurately …and reasonably. Show more

Keywords: Disease treatment plan, big data, knowledge base

DOI: 10.3233/JIFS-179425

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 513-521, 2020

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 523-523, 2020

Authors: Atanassov, Krassimir | Vassilev, Peter

Article Type: Research Article

Abstract: In the present paper we show that Inconsistent intuitionistic fuzzy sets, Picture fuzzy sets and Neutrosophic fuzzy sets are representable by Interval-valued intuitionistic fuzzy sets, which themselves are representable by an ordered pair of the standard Intuitionistic fuzzy sets.

Keywords: Interval-valued intuitionistic fuzzy set, Intuitionistic fuzzy set, Inconsistent intuitionistic fuzzy set, Picture fuzzy set, Neutrosophic fuzzy set

DOI: 10.3233/JIFS-179426

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 525-530, 2020

Authors: Zhang, Wenkai | Gao, Hengxia

Article Type: Research Article

Abstract: Hesitant fuzzy sets (HFSs) is a powerful tool in modelling and managing uncertainty of real-world decision-making problems. As a generalization of HFSs, interval-valued hesitant fuzzy sets (IVHFSs) can model preferences of decision makers with several possible interval values. Within the framework of IVHFSs, this work develops a weakly prioritized multicriteria decision analysis method for addressing problems where there exists a weakly ordered prioritization relationship over criteria. The prioritization relationship between criteria is characterized by the interval-valued hesitant fuzzy weights that are associated with criteria dependence on the satisfaction of the higher priority criteria. First, a novel prioritized scoring operator is …developed to aggregate interval-valued hesitant fuzzy information coming from simultaneous sources with different priority levels. Then, we present an operator-based decision analysis method to address multicriteria decision making problems with weakly prioritized preferences over criteria. Finally, an illustrative example of global mineral investment is provided to show the application of the proposed method. Comparison analyses with existing prioritized multicriteria decision analysis methods show that the proposed method can effectively characterize weakly ordered prioritization relationship over the criteria as well as that it can avoid information loss in eliciting the final recommendations by introducing uncertain weights. Show more

Keywords: Interval-valued hesitant fuzzy sets, weakly prioritized relationships, prioritized scoring operator, multicriteria decision analysis

DOI: 10.3233/JIFS-179427

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 531-543, 2020

Authors: Aydın, Serhat | Yörükoğlu, Mehmet

Article Type: Research Article

Abstract: Ground Handling Services (GHSs) contain detailed services for airplanes and air passengers when they remain on the airport. In this paper, GHSs received by disabled air passengers and the service provider firms were focused. Neutrosophic MULTIMOORA, a newly developed method, has been used for evaluation. Three Turkish GHSs firms are evaluated by eight criteria. The weights of evaluation criteria are determined by Analytic Hierarchy Process. Then algorithm of Neutrosophic MULTIMOORA method is applied to the problem and sensitivity analysis is presented. In the end, the conclusion is given. Contribution of this paper to the literature is using of the Neutrosophic …MULTIMOORA Method firstly for evaluation of GHSs firms. Show more

Keywords: Ground handling services, neutrosophic set, fuzzy logic, MULTIMOORA

DOI: 10.3233/JIFS-179428

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 545-552, 2020

Authors: Bashir, Zia | Rashid, Tabasam | Sałabun, Wojciech | Zafar, Sohail

Article Type: Research Article

Abstract: In this paper, the characterization of Γ -convergence for the first countable topological spaces, characterization of convergence in supremum metric in general setting and some mutual relation between these convergences are discussed. The Γ -convergence is defined as the Kuratowaski-Painlevé convergence of the endographs of the intuitionistic fuzzy sets. The supremum metric is the supremum of Hausdroff distance among the η -cuts of the intuitionistic fuzzy sets. To study these convergences is an important part of the theoretical fundamentals for intuitionistic fuzzy set theory. Some results are given as an application to variational analysis.

Keywords: Intuitionistic fuzzy sets, Pointwise convergence, Γ-convergence, Hausdroff metric, Supremum metric

DOI: 10.3233/JIFS-179429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 553-564, 2020

Authors: Seker, Sukran

Article Type: Research Article

Abstract: Multiple Criteria Decision Making (MCDM) methods have been widely used in literature with different extensions to handle uncertain information for years. The aim of this study is to propose an improved Complex Proportional Assessment (COPRAS) approach by integrating Interval-Valued Pythagorean Fuzzy Set (IVPFS) which is the extension of interval-valued intuitionistic fuzzy set (IVIFS) to deal with MCDM problems in the uncertain environment. It is evident from the previous studies in the literature, extension version of COPRAS method with IVPFSs is first proposed. In order to illustrate the applicability and accuracy of the proposed approach, a real-world application of selecting the …optimal fiber optical access network strategy for Arnavutkoy district in Istanbul is presented. Sensitivity analysis is applied to examine the robustness of the proposed method. A comparative analysis of the proposed method with other existing methods is also conducted. Show more

Keywords: MCDM, uncertainty, COPRAS, IVPFS

DOI: 10.3233/JIFS-179430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 565-575, 2020

Authors: Marcos de Moraes, Ronei | Soares, Elaine Anita de Melo Gomes | Machado, Liliane dos Santos

Article Type: Research Article

Abstract: Classifiers based on Gamma statistical distribution can be found in the scientific literature, but they assume the collected data doesn’t present any errors. However, in some cases, information precision can not be guaranteed, then the fuzzy approach is convenient. Several methods found in the literature are not able to ponder the specific contribution of each class and/or feature for the classification tasks. This paper presents a proposal of a new classifier named Doubled Weighted Fuzzy Gamma Naive Bayes network (DW-FGamNB). This new classifier uses two types of weights in order to allow users to ponder the real contribution of each …class and feature in the classification task. The theoretical development is presented, as well as results of its application on simulated multidimensional data using Gamma statistical distribution. A comparison among DW-FGamNB, Fuzzy Gamma Naive Bayes classifier, classical Gamma Naive Bayes classifier, Naive Bayes classifier, DecionTree-Naive Bayes, Decision Tree C4.5, Logistic Regression, Multilayer Perceptron Neural Network, Adaboost-M1, Radial Basis Function Network and Random Forest was performed. The results obtained showed that the DW-FGamNB produced the best performance, according to the Overall Accuracy Index, Kappa and Tau Coefficients, and diagnostic tests. Show more

Keywords: Gamma statistical distribution, fuzzy classification, fuzzy statistics, double weighted naive bayes

DOI: 10.3233/JIFS-179431

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 577-588, 2020

Authors: Uzun, Ibrahim Mert | Cebi, Selcuk

Article Type: Research Article

Abstract: Risk identification and risk assessment are the most important issues among the occupational health and safety practices. In the industry, the identification of hazards and the risk assessment are often carried out by using subjective risk assessment methods. These methods usually do not provide a perspective on the nature of the measures to be taken. In order to keep sector-specific risks under control, as important as the assessment of risks is to take effective measures against these risks and to continuously monitor the effectiveness of these measures. Therefore, the main objective of this paper is to classify protective and preventive …occupational health and safety measures implemented in the construction sector based on their efficiency by using Fuzzy Kano Model Approach. For this purpose, it is the first time, the feature classes defined by the conventional Kano Model and the Kano Model questionnaire have been reinterpreted in terms of occupational health and safety. Then, the proposed approach has been applied to classify the safety measures utilized in occupational health and safety in terms of their efficiency by using fuzzy Kano Model. According to obtain results, approximately 10% of the control measures which are effectively used at construction site are in Trusting Measure Class. The main contribution of this paper is to provide a new method for analysis of effectiveness of the occupational health and safety measures. Show more

Keywords: Safety measures, fuzzy kano model, accident prevention, construction accidents

DOI: 10.3233/JIFS-179432

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 589-600, 2020

Authors: Ohta, Robison | Salomon, Valerio A.P. | Silva, Messias B.

Article Type: Research Article

Abstract: A multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise comparisons, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in …the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model. Show more

Keywords: Analytic hierarchy process, hesitant fuzzy sets, intuitionistic fuzzy sets, maintenance management

DOI: 10.3233/JIFS-179433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 601-608, 2020

Authors: Türkşen, Özlem

Article Type: Research Article

Abstract: Obtaining interval estimates of nonlinear model parameters is as important as point estimates of model parameters. Because the estimated value of the parameters cannot always be expressed as a single numerical quantity exactly. In this study, it is aimed to propose an interval estimation procedure for nonlinear model parameters with combining soft computing methods instead of using probabilistic assumptions. For this purpose, response and model parameters were presented as triangular fuzzy numbers (TFNs) in nonlinear regression model. The errors were defined as intervals through alpha-cut operations and minimized according to the least absolute deviation (LAD) metric. The novelty of the …study is achieving the minimization in a multi-objective framework in which the objective functions are lower and upper bound of interval type error functions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods were used for multi-objective optimization (MOO) and multi-criteria decision making (MCDM) stages, respectively. Innovatively, in order to obtain reasonable interval estimates, predefined sized compromise solution set was composed and the fuzzy C-means (FCM) clustering algorithm was applied to the compromise set of interval estimates according to the predicted alpha-cut values. The proposed interval estimation approach is applied on a synthetic and a real data sets for application purpose. Show more

Keywords: Interval estimates of nonlinear model parameters, fuzzy nonlinear regression, fuzzy alpha-cut, NSGA-II, TOPSIS, FCM

DOI: 10.3233/JIFS-179434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 609-618, 2020

Authors: Vij, Sonakshi | Jain, Amita | Tayal, Devendra | Castillo, Oscar

Article Type: Research Article

Abstract: The concept of Hesitant Fuzzy Sets (HFS) came into picture where a set is created of the possible membership values that are willing to participate for contribution to the fuzzy sets. HFS has recently become very popular between researchers who are working on variants of fuzzy logic. This paper highlights the research queries related to the Scientometric analysis of HFS by studying 410 research publications from the Web of Science (v.5.31) database (from inception of Web of Science online data till 2017). This paper answers questions pertaining to the important terms and concepts for HFS, co-authorship patterns in HFS, dominating …research areas of HFS, and countries with maximum research paper contribution, co-citation patterns for first authors and bibliographical coupling for organizations. A brief outline of the citation analysis is also made in the form of a sub-section. Show more

Keywords: Fuzzy logic, hesitant fuzzy sets, HFS, Scientometric analysis

DOI: 10.3233/JIFS-179435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 619-626, 2020

Authors: Aydın, Serhat | Kabak, Mehmet

Article Type: Research Article

Abstract: Investment analysis is a process of choosing the best alternative among investment alternatives that provide the best fit for a company. The process contains uncertainty, vagueness, fuzziness and insufficient data; therefore, this evaluating process needs experts’ knowledge and judgments. Fuzzy set theory is a useful technique to capture experts’ evaluations. This paper proposes the new present worth and future worth analysis techniques with single valued neutrosophic set. The proposed techniques allow using possible values of alternatives’ data and membership function of alternatives assigned by experts. The techniques provide the literature with a new multiplication operator and a new term under …the name “neutrosophic equivalent”. An illustrative example shows the applicability of the techniques. Comparison analyses are realized with classical and simplified neutrosophic present and future worth techniques. The comparison results show that the proposed techniques overcome investment analysis problems effectively and efficiently. Show more

Keywords: Investment analysis, present worth analysis, future worth analysis, neutrosophic sets, fuzzy sets

DOI: 10.3233/JIFS-179436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 627-637, 2020

Authors: Nguyen, Hoang

Article Type: Research Article

Abstract: The arithmetic operations on intuitionistic fuzzy sets defined by Atanassov are the most popular in the intuitionistic fuzzy set theory. Based on these operations, many commonly used methods for solving the decision-making (DM) problems under intuitionistic fuzzy environment have been developed and various aggregation operators have been proposed. However, there have been revealed some undesirable properties of these operators, such as the inconsistency with the operations on the ordinary fuzzy sets (FSs), the non-monotonicity of the addition and multiplication operations or non-monotonicity under multiplication by a scalar. We show in this paper that these drawbacks pertain to also the recently …proposed combined aggregations operators such as intuitionistic fuzzy Heronian mean (IFHM), intuitionistic fuzzy interaction partitioned Bonferroni mean (IFIPBM), intuitionistic fuzzy Dombi Bonferroni mean (IFDBM), intuitionistic fuzzy Maclaurin symmetric mean (IFMSM), Pythagorean fuzzy Maclaurin symmetric mean (PFMSM), q-rung orthopair fuzzy power Maclaurin symmetric mean (q-ROFPMSM), Muirhead mean (IFWMM) and intuitionistic fuzzy hybrid weighted arithmetic and geometric aggregation operators (IFHWAGA).This paper proposes some new arithmetic operations on Atanassov’s intuitionistic fuzzy sets that have good algebraic properties, such as idempotency, commutativity, monotonicity and monotonicity under multiplication by a scalar. Based on the proposed operations, the intuitionistic fuzzy weighted arithmetic mean and intuitionistic fuzzy weighted geometric mean operators with the acceptable properties are developed. Some illustrative examples are performed to demonstrate effectiveness and reliability of our method. Finally, in order to verify the validity of the proposed method in solving real-life DM problems, an application example is conducted with a comparative analysis with other existing methods. Show more

Keywords: Intuitionistic fuzzy sets, operations, aggregation operator, decision making

DOI: 10.3233/JIFS-179437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 639-651, 2020

Authors: Goker, Nazli | Dursun, Mehtap | Cedolin, Michele

Article Type: Research Article

Abstract: Companies should cope with uncertain and unpredictable changes while improving responsiveness capability to survive in dynamic market conditions. In recent years, agility concept becomes more and more popular to meet these requirements in management as well as manufacturing. From supply chain viewpoint, collaborating with agile suppliers is principal for constructing an agile supply chain, which is flexible, quick, and responsive. This paper aims to identify the most suitable agile supplier alternative by introducing a novel distance based hierarchical intuitionistic decision making procedure. The proposed methodology, which deals with uncertain and vague data, allows to represent hesitation by using intuitionistic fuzzy …numbers rather than fuzzy numbers that fail to take into account hesitancy. The causal links among evaluation criteria are expressed with intuitionistic fuzzy cognitive map tool that enables to yield the importance degree of each criterion. Moreover, the hierarchical representation of the decision making problem provides an effective analysis with the presence of numerous criteria that are to be considered. The distance based framework is to minimize the distance to the ideal solution while maximizing the distance from the anti-ideal solution in order to determine the most appropriate agile supplier alternative. The case study is conducted in a dye manufacturer that performs in Turkish dye industry. Show more

Keywords: Intuitionistic fuzzy sets, intuitionistic fuzzy cognitive map, hierarchical decision making, agile supplier selection

DOI: 10.3233/JIFS-179438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 653-662, 2020

Authors: Faizi, Shahzad | Rashid, Tabasam | Zafar, Sohail

Article Type: Research Article

Abstract:  The hesitant 2-tuple linguistic set (H2TLS) as an important extension of the 2-tuple linguistic model, can effectively express the judgments of the decision makers (DMs) not only in qualitative aspects but also reflect the vagueness and hesitancy by assigning more than one translation parameters to every linguistic variable of the linguistic term set (LTS). The aim of this study is to extend the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method, to solve multi-criteria group decision making (MCGDM) problems in the context of H2TLSs with completely unknown criteria weights. The TODIM method is developed on the …basis of prospect theory which can effectively capture the psychological behavior of DMs during the decision analysis. In order to enhance the suitability and applicability of H2TLSs, this paper investigates first the generalized distance measure between hesitant 2-tuple linguistic elements (H2TLEs). Furthermore, a score function for H2TLEs is proposed and the dominance relations are defined by using this function. A TODIM method is established that can greatly help in solving MCGDM problems in which alternatives are assessed in the form of H2TLEs in the presence of certain criteria. A procedure for determining the criteria weights is also established as a follow up. Finally, a numerical example is offered and a comparison analysis of proposed extended TODIM method is made with other methods to check the validity and practicality of the proposed study. Show more

Keywords: Hesitant 2-tuple linguistic set, score function, generalized distance measure, multi-criteria group decision making, TODIM method

DOI: 10.3233/JIFS-179439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 663-673, 2020

Authors: Dogan, Onur | Oztaysi, Basar | Fernandez-Llatas, Carlos

Article Type: Research Article

Abstract:  There are some studies and methods in the literature to understand customer needs and behaviors from the path. However, path analysis has a complex structure because the many customers can follow many different paths. Therefore, clustering methods facilitate the analysis of the customer location data to evaluate customer behaviors. Therefore, we aim to understand customer behavior by clustering their paths. We use an intuitionistic fuzzy c-means clustering (IFCM) algorithm for two-dimensional indoor customer data; case durations and the number of visited locations. Customer location data was collected by Bluetooth-based technology devices from one of the major shopping malls in Istanbul. …Firstly, we create customer paths from customer location data by using process mining that is a technique that can be used to increase the understandability of the IFCM results. Moreover, we show with this study that fuzzy methods and process mining technique can be used together to analyze customer paths and gives more understandable results. We also present behavioral changes of some customers who have a different visit by inspecting their clustered paths. Show more

Keywords: Fuzzy c-means clustering, intuitionistic fuzzy sets, process mining, customer behaviors, indoor locations

DOI: 10.3233/JIFS-179440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 675-684, 2020

Authors: Luo, Minxia | Wu, Lixian | Fu, Li

Article Type: Research Article

Abstract: A new distance metric between interval-valued fuzzy sets is proposed. The four special logic metric spaces based on the distance are structured. we analysis and compare the structures of the four logic metric spaces. It is shown that the Łukasiewicz logic metric space and Goguen logic metric space are more suitable for interval-valued fuzzy reasoning. Moreover, the robustness of interval-valued fuzzy reasoning triple I methods are studied in the two logic metric spaces. We prove that fuzzy reasoning triple I methods based on the interval-valued Łukasiewicz residuated implication and interval-valued Goguen residuated implication are robust.

Keywords: Interval-valued fuzzy sets, distance metric, fuzzy metric spaces, triple I method, robustness

DOI: 10.3233/JIFS-179441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 685-696, 2020

Authors: Bayram, Mehmet | Akat, Muzaffer | Bulkan, Serol

Article Type: Research Article

Abstract: Pairs trading is a widespread market-neutral trading strategy aiming to utilize the relationship between pairs of financial instruments in efficient markets, where predictability of separate asset movements is theoretically not possible. The implication of trading pairs, following statistical analysis, is to buy the underpriced asset while short selling the overpriced. The predicted price relationship is determined through analysis of historical spread data between the members of the corresponding pair. The investor expects the price difference, in an efficient market, should converge and stocks return to their ‘fair value’, where the positions are closed and profit is realized. The main focus …of this study is the contribution of the fuzzy engine to the existing pairs trading strategy. Widespread classical ‘crisp’ technique is chosen, utilized and compared with the developed ‘fuzzy’ model throughout the paper. In order to further improve this contribution, the expert opinions extracted from the Bloomberg database are also integrated into the fuzzy decision-making process. In most studies, transaction costs are simply ignored. As a final robustness check, the transaction costs are also considered. The improvement reached by the developed fuzzy technique is observed to be even more remarkable in this case. Show more

Keywords: pairs trading, algorithmic trading, fuzzy statistical arbitrage

DOI: 10.3233/JIFS-179442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 697-707, 2020

Authors: López-Medina, M.A. | Espinilla, M. | Cleland, I. | Nugent, C. | Medina, J.

Article Type: Research Article

Abstract: Fog Computing is an approach involving smart devices. These devices carry out data processing to provide collaborative services to reach a common goal, usually, in the cloud. In the fog computing paradigm, uncertainty and vagueness are inherent to the data processing due to the limitations of computational and communication capabilities of the smart devices. Fuzzy logic and protoforms represent a powerful tool to model and compute imprecise data presented within the fog-computing paradigm. In this paper, we present a fuzzy cloud-fog approach based on fuzzy temporal windows and fuzzy aggregation. The innovations of this paper are: i) to model the …uncertainty involved in fog nodes linguistically, ii) to compute and distribute relevant linguistic information (protoforms), and iii) to publish the computed protoforms in the cloud to generate complex protoforms, which reach the common goal. This new fuzzy cloud-fog approach is applied to the problem of activity recognition in smart homes. In this context, the smart devices in a smart home are represented by fog nodes, which cooperate for activity recognition using a fuzzy cloud-fog computing approach to provide solutions in ambient-assisted living. Finally, to demonstrate the effectiveness of the proposal in handling situations/environments where multiple and heterogeneous devices are involved (such as UWB beacons, smart objects and smart wearable devices), a case study of the proposed fuzzy cloud-fog approach is implemented in the smart lab of the University of Jaén. So, the results obtained with the proposed approach in the case study are compared to the results obtained with a non-fuzzy approach with the aim of showing the advantages of the fuzzy methodology. Show more

Keywords: Fuzzy fog computing, fuzzy cloud computing, smart devices, UWB technology, activity recognition, protoforms, fuzzy temporal windows, fuzzy aggregation

DOI: 10.3233/JIFS-179443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 709-721, 2020

Authors: Yörükoğlu, Mehmet | Aydın, Serhat

Article Type: Research Article

Abstract: The Industrial Revolution, which started with steam machines, has evolved into intelligent systems in which objects speak to each other in the name of Industry 4.0. Smart containers (SC), which are the latest in this evolution of containers and one of the key elements of logistic in Supply Chain Management System (SCMS), stand out with their flexibility, traceability, and contribution to the optimization of the supply chain. In this paper the existing properties of the currently evolving smart containers are compiled and the users’ needs that will guide future designs are determined. In the application section, three different smart containers …are evaluated according to seven different conflicting criteria in neutrosophic environment. By using neutrosophic TOPSIS method relative closeness coefficient of alternatives are calculated. Finally alternatives are ranked in descending order. The originality of the paper is that smart containers evaluation problem is handled by the neutrosophic MCDM method for the first time in the literature. Show more

Keywords: Industry 4.0, smart container, multi criteria decision making, neutrosophic TOPSIS

DOI: 10.3233/JIFS-179444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 723-733, 2020

Authors: Labella, Álvaro | Rodríguez, Rosa M. | Martínez, Luis

Article Type: Research Article

Abstract: Group Decision Making (GDM) deals with decision problems in which multiple experts, with their own attitudes and knowledge, evaluate different alternatives or solutions with the aim of achieving a common solution. In such cases disagreements can appear, which might led to failed solutions. To manage such conflicts, Consensus Reaching Processes (CRPs) have been added to the GDM solving process. GDM problems under uncertainty often model uncertainty by linguistic descriptors, being most of linguistic based CRPs based on the use of single linguistic terms for modelling experts’ opinions, which cannot be expressive enough in some situations because of either the uncertainty …involved or the experts’ hesitancy. Therefore, this paper aims to fill this gap by proposing a novel consensus model dealing with GDM problems in which experts’ preferences are elicited by means of Comparative Linguistic Expressions (CLEs) based on Hesitant Fuzzy Linguistic Term Sets, which allow to model the experts’ hesitancy in a flexible way. Furthermore, CLEs are modelled by fuzzy membership functions in order to keep the fuzzy representation in the whole CRP and preserve as much information as possible. Additionally, the proposed model is implemented and integrated in an intelligent CRP support system, so-called AFRYCA 3.0 to carry out a case study about this new CRP and compare it with previous models. Show more

Keywords: group decision making, comparative linguistic expressions, hesitant fuzzy linguistic term sets, consensus reaching process

DOI: 10.3233/JIFS-179445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 735-748, 2020

Authors: Kahraman, Cengiz | Oztaysi, Başar | Cevik Onar, Sezi

Article Type: Research Article

Abstract: Neutrosophic sets are an extension of intuitionistic fuzzy sets, providing a new approach to uncertainty with their three components: Truth, indeterminacy, and falsity. These parameters can be assigned independently which makes their sum equal to at most three. Neutrosophic sets have been extensively employed in the new extensions of multicriteria decision making methods (MCDM) in the literature. Law firms who are business entities formed by one or more lawyers are associations of lawyers who practice law. We propose a neutrosophic analytic hierarchy process (NAHP) for comparing the performances of these law firms in this paper. The performance of law offices …is comparatively measured by the proposed NAHP. Linguistic assessments are used in this process rather than exact numerical evaluations. The illustrative problem hierarchy includes four criteria and four alternatives are given. Show more

Keywords: Single-valued neutrosophic sets, interval-valued neutrosophic sets, AHP, outsourcing, law firm, MCDM

DOI: 10.3233/JIFS-179446

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 749-759, 2020

Authors: Guleria, Abhishek | Bajaj, Rakesh Kumar

Article Type: Research Article

Abstract: In the present communication, a new (R , S )-norm discriminant measure of Pythagorean fuzzy sets has been proposed along with its various properties. Monotonic behavior with respect to the parameters R & S and their proof of validity have also been studied. Methodologies and necessary steps of the algorithms for various decision-making problems viz. pattern recognition problem, medical diagnosis problem and multi criteria decision-making problem have been outlined on the basis of the proposed information measure. For the sake of illustration, numerical example for each case has been provided. A comparative analysis for the considered applications has …also been studied in contrast with the popular existing methodologies stating important observations and advantages. Show more

Keywords: Pythagorean fuzzy set, discriminant measure, monotonicity, pattern recognition, medical diagnosis, multiple criteria decision making

DOI: 10.3233/JIFS-179447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 761-777, 2020

Authors: Deli, Irfan

Article Type: Research Article

Abstract: Selecting an appropriate robot among the alternative robots is a difficult problem for decision makers, since it is complicated to express attributes as crisp numbers in multiple attribute decision making problems. Generalized trapezoidal hesitant fuzzy numbers(GTHF-numbers) can be efficiently used to estimate information in the decision making process. This paper proposes an advanced type of TOPSIS (Technique for order preference by similarity to ideal solution) method, called TOPSIS method of GTHF-numbers. To do this, we introduce some novel distance measures including Hamming distance measure, Euclidean distance measure, λ -generalized distance measure, λ -generalized Hausdorff distance measure, γ -hybrid Hamming distance, …hybrid Euclidean distance and λ -generalized hybrid distance measure on GTHF-numbers. Then, we develop a novel TOPSIS method of GTHF-numbers based on introduced distance measures. Finally, we provide a real example, for an auto company which desires to select a suitable robot for its production process, based on the proposed TOPSIS method of GTHF-numbers to prove the efficiency and the applicability of the proposed method. Show more

Keywords: Hesitant fuzzy set, generalized trapezoidal hesitant fuzzy number, distance measures, TOPSIS method, multiple attribute decision making, robot selection

DOI: 10.3233/JIFS-179448

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 779-793, 2020

Authors: Bashir, Zia | Abbas Malik, M.G. | Asif, Saba | Rashid, Tabasam

Article Type: Research Article

Abstract: In this paper, an in depth study is done on topological properties of intuitionistic fuzzy rough sets in light of different conditions like serial, strongly serial, left continuity, transitivity on intuitionistic fuzzy relations, t-norms, implicators by adopting a axiomatic approach with the ingredients of intuitionistic fuzzy logic. Numerous intuitionistic fuzzy topologies based on many different kinds of intuitionistic fuzzy relations are explored. Also, a special class of intuitionistic fuzzy relations known as T -similarity class has been studied algebraically and found interesting lattices to model real life problems for better applications of intuitionistic fuzzy rough sets.

Keywords: Intuitionistic fuzzy rough sets, intuitionistic fuzzy topologies, intuition fuzzy logic, lattices

DOI: 10.3233/JIFS-179449

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 795-807, 2020

Authors: Oztaysi, Başar | Cevik Onar, Sezi | Kahraman, Cengiz

Article Type: Research Article

Abstract: The education system is very important for the society. In this study, we try to define and prioritize the requirements of an n online platform which can be used as a source for collecting feedback from stakeholders of an educating system. The involved stakeholders are the course content generators, teachers, students and families of the students. In the application three experts used linguistic terms to evaluate the performance indicators and the weights are calculated using Pythagorean Fuzzy Analytic Hierarch Process (AHP) Method.

Keywords: System design, fuzzy sets, pythagorean fuzzy sets, analytic hierarchy process

DOI: 10.3233/JIFS-179450

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 809-819, 2020

Authors: Castillo, Oscar | Kutlu, Fatih | Atan, Özkan

Article Type: Research Article

Abstract: This paper proposes an intuitionistic fuzzy control method for twin rotor multi-input and multi-output (twin rotor MIMO) systems. Twin rotor MIMO systems are often used to measure the performance of control systems as they are extremely sensitive to environmental factors. The use of the intuitionistic fuzzy control method for modeling these uncertainties offers an effective way to increase the robustness of the control system to uncertainties in the structure of twin rotor MIMO systems. In this study, two intuitionistic fuzzy controllers are designed, namely for the main and tail rotors separately and then combine the outputs of these rotors. Also, …this method is compared with the classical optimal PID method in terms of stability and performance by various simulations and experiments. Show more

Keywords: Fuzzy and intuitionistic fuzzy set, intuitionistic fuzzy control, twin rotor MIMO

DOI: 10.3233/JIFS-179451

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 821-833, 2020

Authors: Otay, İrem | Jaller, Miguel

Article Type: Research Article

Abstract: This study focuses on the evaluation of disaster risk management and response (DRMR) processes and capabilities using a multi-expert multi-criteria decision making (MCDM) framework. The proposed framework considers four sets of evaluation and performance criteria: risk knowledge and organization, risk reduction, disaster response management, and disaster response support; and 22 sub-criteria such as regulating risk management, financial management, energy, and public safety. To contend with random perception and utility, lack of information and subjectivity in the human (expert) judgment processes that could be present in expert-based models, the authors propose an interval-valued intuitionistic fuzzy sets (IVIFSs) approach. IVIFSs can handle …high levels of uncertainty and define appropriate membership functions. Specifically, the proposed approach incorporates score judgement and possibility degree matrices, and estimates the local and global weights for each assessment criteria. And finally, evaluates the overall performances of the alternatives using intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The authors implemented the framework to the Atlantico State of Colombia, and assessed the disaster risk management and response processes for each for the State’s 23 municipalities. The authors discuss sensitivity analysis that illustrates the robustness of the results. Show more

Keywords: Disaster management, risk management, interval-valued intuitionistic fuzzy sets, MCDM, TOPSIS

DOI: 10.3233/JIFS-179452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 835-852, 2020

Authors: Parimala, M. | Karthika, M. | Jafari, Saeid | Smarandache, Florentin | El-Atik, A.A.

Article Type: Research Article

Abstract:  Neutrosophic topological space is an extension of intuitionistic topological space and each triplet set in neutrosophic topological space contains membership, indeterminacy and non-membership values. Connected set in intuitionistic topological set contains membership and non-membership values and inderterminacy have not discussed in that set. This motivates the authors to propose this novel concept called neutrosophic αψ -connectedness. So we introduce the new notion of neutrosophic αψ -connectedness in neutrosophic topological spaces and investigate some properties of neutrosophic αψ -connectedness between sets and subsets of two sets. Some properties of this concept presented with numerical quantities to prove the non-existence.

Keywords: Neutrosophic closed set, Neutrosophic αψ-closed set, Neutrosophic αψ-connectedness between neutrosophic sets

DOI: 10.3233/JIFS-179453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 853-857, 2020

Authors: Büyüközkan, Gülçin | Havle, Celal Alpay | Feyzioğlu, Orhan | Göçer, Fethullah

Article Type: Research Article

Abstract: Transportation becomes increasingly important for global trade, mobility, and economies. Passengers expect speed and quality from transportation services. As a result, the demand for air transportation is steadily rising. Higher demand for flights brings along new expectations and competition. In particular, airline companies are focused on service quality, knowing that it is a necessity to survive in a competitive market by meeting customer expectations. Hence, it is aimed that to analyze Airline Service Quality (ASQ) in Turkey. A SERVQUAL based model is developed and the criteria of the model is analyzed using group decision making (GDM) based intuitionistic fuzzy cognitive …map (IFCM) approach. A real case is conducted in Turkey airline industry. By considering the hesitation, uncertainty and intuition of decision-making processes and the opinions of the decision makers, classical FCM approach is expanded to IF environment. Decision makers who are experts in Turkey airline industry, evaluate the relationship between the criteria. The importance ratings of the criteria are determined. Thanks to dynamic structure of IFCM, scenario analysis is performed to make strategic decisions. Originality of the paper is that it is the first study dealing with GDM based IFCM and SERVQUAL approach for ASQ in Turkey to the best of our knowledge. Show more

Keywords: Airline service quality, group decision making, intuitionistic fuzzy cognitive map, scenario analysis, SERVQUAL

DOI: 10.3233/JIFS-179454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 859-872, 2020

Authors: Abdullah, Lazim | Goh, Chunmin | Zamri, Nurnadiah | Othman, Mahmod

Article Type: Research Article

Abstract: The technique for order preference by similarity to ideal solution (TOPSIS) has been applied to numerous multi-criteria decision making (MCDM) problems where crisp numbers are utilised in defining linguistic evaluation. The interval valued intuitionistic fuzzy TOPSIS (IVIF TOPSIS) can offer a new decision making method in solving MCDM problems where interval valued intuitionistic fuzzy sets are utilised in defining linguistic terms. Differently from the TOPSIS, which directly utilised crisp numbers, this method introduces upper and lower intervals of memberships to capture wide arrays of uncertain and fuzzy information. In this paper, criteria and alternatives in flood management is investigated where …the best alternative in flood mitigation approach can be identified using the IVIF TOPSIS. Four decision makers in flood management were invited to provide linguistic evaluation of seven alternatives with respect to seven criteria. Computational results indicate that the alternative ‘pumping station’ is identified as the best alternative of flood mitigation project. The findings of this study would benefit authority in suggesting the effective approach in flood mitigation initiatives. Show more

Keywords: TOPSIS, interval valued intuitionistic fuzzy set, linguistic evaluation, decision making, flood management

DOI: 10.3233/JIFS-179455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 873-881, 2020

Authors: Onar, Sezi Cevik | Oztaysi, Basar | Kahraman, Cengiz | Ozturk, Ersan

Article Type: Research Article

Abstract: Managing the collection of unpaid debts is crucial for the financial survival of the companies. The long term unpaid debts are collected through legal debt collection processes. This legal process should be carried out by qualified lawyers. The companies with many subscribers usually work with legal debt collection offices outside the company rather than allocate internal resources for the management of this process. Evaluating the performances of legal debt collection offices and appropriate distribution of the relevant debtor files to different legal debt collection offices located in different regions are very important for optimizing the debt collection. One of the …biggest GSM operators in Turkey that has millions of customers wants to enhance its legal debt collection process. Due to the high number of customer, the GSM operator works approximately one hundred legal debt collection offices which makes evaluation complex. This complex evaluation process should be objective, transparent, and represent the company vision and strategy. The legal debt collection offices should not only increase the total amount of collected debts but also avoid creating compliance problems and customer dissatisfaction. The evaluation of legal debt collection offices should involve both of these objective and subjective criteria. Yet, the evaluations involve hesitancy and vagueness. In this study, we use hesitant Pythagorean fuzzy sets for evaluating the performances of the legal debt collection offices and apply it the real data. Show more

Keywords: Pythagorean fuzzy sets, Legal debt collection, Pythagorean AHP, Intuitionistic Type 2

DOI: 10.3233/JIFS-179456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 883-894, 2020

Authors: Diao, Hongyue | Cao, Yiming | Xu, Yingying | Zou, Li | Deng, Ansheng

Article Type: Research Article

Abstract: The group decision-making is a process that multiple experts participate in analysis and decision-making for multiple attributes, which can assist decision makers to set priorities and make the best decision. The linguistic truth-valued intuitionistic fuzzy lattice can better express both comparable and incomparable linguistic information, which can also better to deal with positive and negative linguistic information at the same time. To deal with the decision-making problem with fuzzy linguistic information, we propose an approach for group decision making based on linguistic truth-valued intuitionistic fuzzy lattice. For the comparable fuzzy linguistic information, the linguistic truth-valued intuitionistic fuzzy weighted averaging operator …and the linguistic truth-valued intuitionistic fuzzy ordered weighted averaging operator are presented to aggregate evaluation information of multiple experts. For the incomparable fuzzy linguistic information, positive reference nearness degree and negative reference nearness degree are introduced to deal with incomparable result with different preferences. We discuss an algorithm of group decision making, in which the decision results are alternative according to the decision makers’ preferences. A practical example is provided to illustrate the validity and rationality of the developed approach. Show more

Keywords: Group decision making, linguistic truth-valued intuitionistic fuzzy lattice, linguistic truth-valued aggregation operator

DOI: 10.3233/JIFS-179457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 895-904, 2020

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, an intelligent approach is presented for the evaluation and selection of innovation projects. Selecting the best innovation project is a complicated multiple criteria decision making (MCDM) problem with several potentially competing quantitative and qualitative criteria. In this paper, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (hesitant F-VIKOR) are integrated to evaluate and rank innovation projects. In the hesitant fuzzy AHP-VIKOR, hesitant F-AHP is used to find fuzzy evaluation criteria weights and hesitant F-VIKOR is implemented to rank innovation project alternatives. A numerical example is …given where five innovation projects are evaluated based on nine criteria by three decision makers. Show more

Keywords: Innovation project selection, fuzzy, multiple-criteria decision making, AHP, VIKOR

DOI: 10.3233/JIFS-179458

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 905-915, 2020

Authors: Bashir, Kamal | Li, Tianrui | Yohannese, Chubato Wondaferaw | Yahaya, Mahama

Article Type: Research Article

Abstract: The object of Software Defect Prediction (SDP) is to identify modules that are prone to defect. This is achieved by training prediction models with datasets obtained by mining software historical depositories. When one acquires data through this approach, it often includes class imbalance which has an unequal class representation among their example. We hypothesize that the imbalance learning is not a problem in itself and decrease in performance is also influenced by other factors related to class distribution in the data. One of these is the existence of noisy and borderline examples. Thus, the objective of our research is to …propose a novel preprocessing method using Synthetic Minority Over-Sampling Technique (SMOTE), Fuzzy-rough Instance Selection type II (FRIS-II) and Iterative Noise Filter based on the Fusion of Classifiers (INFFC) which can overcome these problems. The experimental results show that the new proposal significantly outperformed all the methods compared in this study. Show more

Keywords: Software defect prediction, data sampling, fuzzy rough set, noise filtering

DOI: 10.3233/JIFS-179459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 917-933, 2020

Authors: Çolak, Murat | Kaya, İhsan | Özkan, Betül | Budak, Ayşenur | Karaşan, Ali

Article Type: Research Article

Abstract:  Nowadays, more companies are trying to implement blockchain technology (BT) that enables to increase the quality of the products/services to their supply chains in order to improve their performance. BT can be applied to different sectors according to their specific needs. Evaluation of BT with respect to sectors needs considering several factors and it can be considered as a multi criteria decision making (MCDM) problem. In this paper, the appropriateness of BT in Supply Chain Management (SCM) according to different sectors has been evaluated by using a MCDM methodology based on hesitant fuzzy sets (HFSs). The suggested MCDM methodology consists …of Delphi method, hesitant fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HF-TOPSIS) methods. In the first stage, the criteria and sub-criteria utilized for performance evaluation of BT in supply chain management have been determined by using Delphi method. The weights of main and sub-criteria have been obtained through HF-AHP method and finally, the alternative sectors have been ranked according to results of HF-TOPSIS method. For this aim, a hierarchical MCDM problem that consists of 5 main and 17 sub-criteria has been created and the alternative sectors have been evaluated. As a result, medicine/drug and jewelry sectors have been respectively determined as the most and the least suitable alternatives in order to implement BT by means of the proposed HFSs based methodology. Finally, a sensitivity analysis has been conducted to show the importance of the main criteria weights on ranking of alternatives. Show more

Keywords: Blockchain technology, supply chain management, hesitant fuzzy sets, AHP, TOPSIS

DOI: 10.3233/JIFS-179460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 935-946, 2020

Authors: Piltan, Farzin | Kim, Jong-Myon

Article Type: Research Article

Abstract: The design of an effective procedure for leak detection, estimation, and leak size classification is necessary to maintain the healthy and safe operations of pipelines for conveying fluids and gas from one place to another. The complexities of nonlinear and uncertain behavior inherent in a pipeline lead to difficulty of detection, estimation, and leak size estimation. Hence, a robust hybrid leak detection and size estimation method based on the back stepping hyperbolic Takagi-Sugeno (T-S) fuzzy sliding mode extended ARX-Laguerre Proportional Integral (PI) observer for pipelines is presented. Because of the effects of gases and fluids in pipelines, accurate physical modeling …of a pipeline is difficult. Consequently, the ARX-Laguerre technique is used for pipeline modeling in this study. Early detection of leaks is important to avoid product loss and other severe damage. To address this issue, the extended ARX-Laguerre PI observer is utilized to detect and estimate a leak. In addition, a T-S fuzzy technique is applied to an extended ARX-Laguerre PI observer to improve leak estimation in the presence of uncertainties. Thus, the T-S fuzzy sliding mode extended ARX-Laguerre PI observer adaptively improves the reliability, robustness, and estimation accuracy of leak detection and estimation. To leak size classification in the presence of uncertainties, the hyperbolic differential equations are governed by the T-S fuzzy extended ARX-Laguerre PI observer to find the exact solution for the kernels of a backstepping-based leak boundary. The leak estimation convergence error shows that the leak size estimation can be calculated independent of the location of the leak, which is the main contribution of this research. It is assumed that pressure and flowmeter sensors are available at the inlet and outlet of the pipeline. The effectiveness of the proposed robust backstepping hyperbolic T-S fuzzy sliding mode extended ARX-Laguerre PI observer was tested over an experimental dataset. According to the results, the proposed technique improved the leak detection, estimation, and size estimation. Show more

Keywords: Pipeline, T-S fuzzy algorithm, sliding mode technique, ARX-Laguerre system estimation, PI observer, leak detection, leak estimation, leak size classification, partial differential equation, backstepping algorithm

DOI: 10.3233/JIFS-179461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 947-961, 2020

Authors: Kutlu Gündoğdu, Fatma

Article Type: Research Article

Abstract:  The three dimensional extensions of ordinary fuzzy sets such as intuitionistic fuzzy sets (IFS), Pythagorean fuzzy sets (PFS), and neutrosophic sets (NS) aim at collecting experts’ judgments based on membership, non-membership and hesitancy degrees. Generalized three-dimensional spherical fuzzy sets have been introduced to the literature, including their arithmetic operations, aggregation operators, and defuzzfication operations. Expansion of classical Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form (MULTIMOORA) has been performed by using ordinary fuzzy, hesitant fuzzy, intuitionistic fuzzy, and neutrosophic sets in the literature. I aim at developing the spherical fuzzy MULTIMOORA method since the spherical fuzzy point …of view can contribute to this multicriteria decision environment. By using spherical fuzzy sets (SFS), the MULTIMOORA method can be more efficient for solving complex problems, which require evaluation and estimation under unreliable data environment. The validation of the proposed approach is shown through an illustrative example. Additionally, comparative analyses with neutrosophic MULTIMOORA and intuitionistic fuzzy TOPSIS methods are presented. Show more

Keywords: Spherical fuzzy sets, multicriteria decision making, MULTIMOORA, personnel selection, TOPSIS

DOI: 10.3233/JIFS-179462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 963-978, 2020

Authors: Yatsalo, Boris | Korobov, Alexander | Öztayşi, Başar | Kahraman, Cengiz | Martínez, Luis

Article Type: Research Article

Abstract: Within Multi-Criteria Decision Analysis (MCDA), the TOPSIS method and its fuzzy extensions, fuzzy TOPSIS (FTOPSIS) models, are widespread ones for solving multi-criteria decision problems. At the same time, FTOPSIS models, as a rule, are implemented based on approximate computations with the use of triangular and trapezoidal fuzzy numbers. This paper introduces a novel approach to fuzzy extension of TOPSIS with the use of fuzzy criteria values and fuzzy weight coefficients of the general type and implementing functions of fuzzy numbers based on standard fuzzy arithmetic and transformation methods. Within FTOPSIS, for ranking of fuzzy numbers/alternatives the concept of Fuzzy Multi-criteria …Acceptability Analysis (FMAA) is implemented. The use of FMAA within Fuzzy MCDA (FMCDA) represents a systematical implementation of the concept of fuzzy decision analysis that “the decision taken in the fuzzy environment must be inherently fuzzy”. FTOPSIS-FMAA model not only allows ranking the set of alternatives, but also provides the confidence measure for the rank obtained by this model. This approach also considers the overestimation problem, which arises within FMCDA and FTOPSIS-FMAA implementation. A case study on a multi-criteria housing development decision problem is introduced and explored by several FTOPSIS-FMAA models. Finally, a comparison of different FTOPSIS-FMAA models is implemented with the use of Monte Carlo simulation. Show more

Keywords: Fuzzy number, fuzzy preference relation, ranking of fuzzy numbers, MCDA, TOPSIS, fuzzy TOPSIS, FMAA, overestimation

DOI: 10.3233/JIFS-179463

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 979-995, 2020

Authors: Beskese, Ahmet | Camci, Alper | Temur, Gul Tekin | Erturk, Ercan

Article Type: Research Article

Abstract:  As energy security concerns push the countries to find more sustainable and renewable sources of energy, wind power became one of the fastest growing renewable energy source. As only a handful of wind turbine manufacturers established foothold in world markets, it is essential for managers to make right decisions regarding which wind turbines they will install in any given project. This study explores the literature on the wind turbine selection, solicits opinions of the industry experts to come up with a more realistic set of criteria and develops a decision making tool integrating hesitant fuzzy Analytic Hierarchy Process (AHP) with …Technique-for-Order-Preference-by-Similarity-to-Ideal-Solution (TOPSIS). As wind turbine selection problem includes both quantitative and qualitative criteria, it is difficult to tackle with high uncertainty by using traditional techniques. Thus, hesitant fuzzy sets (HFS) which is an evolved fuzzy tool that deals with vagueness is utilized. In this study, hesitant fuzzy AHP is utilized to overcome the ambiguity, which occurs during criteria prioritization. In order to rank the alternatives, hesitant fuzzy TOPSIS is applied. By the help of this integrated approach, evaluation process becomes systematic and easy to deal with vagueness. The proposed method is demonstrated by a case study in Turkey. Show more

Keywords: Wind turbine, hesitant fuzzy sets, hesitant fuzzy analytic hierarchy process, hesitant fuzzy TOPSIS, multi criteria decision making

DOI: 10.3233/JIFS-179464

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 997-1011, 2020

Authors: Demircioğlu, M. Emre | Ulukan, H. Ziya

Article Type: Research Article

Abstract: Due to the industrial emissions, poor disposal of wastes, mining, deforestation, increased use of fossil fuels and vicious agricultural activities, environmental pollution rapidly arises and becomes one of the most serious problems of the contemporary world. Humanity tries to abstain from living in polluted cities because of its effects adversely to quality of life. As the utilization of Multi-Criteria Decision Making (MCDM) techniques plays a key role in choosing the most suitable option between all feasible alternatives, this work proposes a hybrid MCDM method to rank the major cities from the least polluted to the most polluted according to the …types of pollution. Owing to the capability to tackle imprecise and uncertain decision information, intuitionistic fuzzy (IF) sets are employed as well as some of the important properties of these concepts are studied. An integrated method combines IF Simple Additive Weighting (IF-SAW) for determining the weights of the types of pollution and IF Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) technique for ranking the major cities. In ranking phase, modification and improvement of classical PROMETHEE into the IF environment is accurately implemented. A Group Decision Making (GDM) process which deals with both quantitative and qualitative factors in an uncertain environment is developed. The effectiveness and applicability of the proposed methodology is numerically illustrated with real world data of environmental pollution in major cities and the study showed that IF-PROMETHEE method could be used in environmental pollution problem as an efficient method. Show more

Keywords: Intuitionistic fuzzy sets, multi criteria group decision making, PROMETHEE, SAW

DOI: 10.3233/JIFS-179465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1013-1025, 2020

Authors: Oner, Sultan Ceren | Oztaysi, Başar | Oner, Mahir

Article Type: Research Article

Abstract: The improvements in mobile technologies led to the wide adaptation and triggered the demand for location based services. In this respect, examining user similarities enable the analysis of user interests in terms of the determination of purchasing preferences and actual needs. User similarities are generally extracted from consumer life style, demographical information or the reflections from previously sent messages. In spite of the fact that these factors may not directly influence the purchasing decision, uncertain or lack of information can be encountered while establishing recommendation systems. Thus, researchers try to search other indicators that can reflect customer characteristics from spatial …data, digital contribution in social media and search history for preferable representation of the changes in purchasing tendency. In this study, social platform based interval valued intuitionistic fuzzy location recommendation system is proposed by considering three common social platforms: Trip Advisor, Zomato and Foursquare. To perform restaurant offers to appropriate social platform users, a sentiment analysis is conducted to selected restaurants and number of negative, positive and neutral comments are extracted. After that, restaurant and location information are examined by using user, restaurant and location clustering via fuzzy clustering. Finally, intuitionistic fuzzy similarity matrix based collaborative filtering is used for restaurant offers to similar users. Show more

Keywords: Location based systems, recommendation systems, interval valued intuitionistic fuzzy sets

DOI: 10.3233/JIFS-179466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1027-1042, 2020

Authors: Yildiz, Didem | Temur, Gul Tekin | Beskese, Ahmet | Bozbura, Faik Tunc

Article Type: Research Article

Abstract:  In contemporary business world, employees are one of the core competencies of organizations and to attract, retain, and engage talented employees is crucial for organizations for sustainable success. Understanding and leveraging employee experience is one of the tending topics for organizations because positive employee experience affects employees’ attachment, engagement and loyalty to the organization. Human resource management departments and leaders can apply different strategic initiations to boost employee experience in their organizations. In this study, we aim to design an integrated model for leaders and organizations to guide them for creating positive employee experience to have engaging, enjoyable, and productive …work environment. The integrated model includes two phases: (1) evaluation of criteria affecting positive employee experience by hesitant fuzzy analytic hierarchy process (HFAHP) and (2) developing a practical scoring procedure to help companies with their self-assessments by using fuzzy simple additive weighting (FSAW) method. In the first phase, four main and sixteen sub-criteria are taken into consideration. For the second phase, the application of the integrated model is demonstrated with a numerical example from real world. The results indicate that for positive employee experience, leadership has the highest importance followed by human capitals’ development opportunity, positive organizational culture, and communication. Show more

Keywords: Employee experience, employee engagement, hesitant fuzzy sets, hesitant fuzzy analytic hierarchy process, fuzzy simple additive weighting, multi criteria decision making

DOI: 10.3233/JIFS-179467

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1043-1058, 2020

Authors: Cayir Ervural, Beyzanur

Article Type: Research Article

Abstract: Energy efficiency initiatives are now more noteworthy due to awareness and sensitivity in the use of resources in rational, optimal and effective ways. The uncertain and dynamic structure of the electricity distribution market requires continuous improvement and efficiency activities/strategic decisions by adding new investments. Energy efficiency assessment plays an important role in improving energy efficiency. In this study, Data Envelopment Analysis (DEA) was employed to investigate the efficiency performance of twenty-one electricity distribution companies in Turkey. The results of DEA revealed that seven of the twenty-one electricity distribution companies were efficiently attempted in Turkey. After utilizing the DEA model, an …Artificial Neural Network (ANN) method based on DEA was constructed, and then the efficiency of each company was predicted. According to the proposed integrated model, with incorporating new/alternative electricity companies, investment plans can be easily evaluated from a real perspective, and their performances can be predicted accurately. The study is expected to assist direct energy decision-makers and investors and help them in their investment plans. Show more

Keywords: Electricity distribution market, data envelopment analysis, artificial neural network

DOI: 10.3233/JIFS-179468

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1059-1069, 2020

Authors: Onar, Sezi Çevik | Kahraman, Cengiz | Öztayşi, Başar | Boltürk, Eda

Article Type: Research Article

Abstract:  The problems in the production systems often involve complexity and imprecision. The traditional techniques can be insufficient to handle such problems. This uncertainty and vagueness can be treated with the fuzzy sets. The fuzzy sets are frequently utilized to optimize production system problems under imprecise, complex and subjective information. It is important to gain academic knowledge on how fuzzy sets and the new developments in the fuzzy set theory are utilized in production systems. In this study, we develop a state-of-the-art literature review for the usage of fuzzy sets in production system problems. The literature review is based on 3147 …publications composed of 1832 articles, 1277 conference papers and 38 book chapters indexed by Scopus. We present the tabular and graphical results of the literature review. The literature review indicates that although both production literature and fuzzy literature have an increasing attention, at some areas of production systems fuzzy sets have limited usage. Show more

Keywords: Production research, information management, fuzzy sets, intuitionistic fuzzy sets, type-n fuzzy sets, hesitant fuzzy sets, pythagorean fuzzy sets

DOI: 10.3233/JIFS-179469

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1071-1081, 2020

Authors: Dogu, Elif | Albayrak, Y. Esra | Tuncay, Esin

Article Type: Research Article

Abstract: Tuberculosis (TB) bacteria may develop resistance to the drugs, which are used in TB treatment. Multidrug-resistant TB (MDR-TB) is a type of TB that does not respond to at least rifampicin and isoniazid, the 2 most powerful anti-TB drugs. MDR-TB requires a more compelling treatment and it is more difficult to diagnose. The experience of physician is the key factor in the success of MDR-TB diagnose. The existence of TB bacteria in the body can be observed relatively faster with a standard sputum smear however, drug-susceptibility tests require nearly 45 days. To cope with this infectious disease, it is vital …to estimate the resistance in a newly diagnosed TB patient to plan the initialization of the treatment in the testing period. Herein, the purpose of this study is to build a framework and establish a mathematical model that will help decision makers (physicians) while estimating the risk of multidrug resistance when a new tuberculosis patient arrives, using intuitionistic fuzzy cognitive maps (IFCM). Intuitionistic fuzzy sets are utilized to reflect the decision makers’ hesitancy degrees in the model. Show more

Keywords: Multidrug-resistant tuberculosis, intuitionistic fuzzy cognitive maps, medical decision support, risk factors

DOI: 10.3233/JIFS-179470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1083-1095, 2020

Authors: Kaya, Aycan | Çiçekalan, Büşra | Çebi, Ferhan

Article Type: Research Article

Abstract: With the increasing environmental concerns, new regulations to decrease Waste Electric and Electronic Equipment (WEEE) have taken effect in many countries. Recycling is an important part of the challenge with the increasing amount of waste by time. Therefore, this study aims to investigate the facility location problem of WEEE recycling plant. Taking into consideration the requirement of the process to consider several conflicting factors from qualitative to quantitative factors, one of the MCDM techniques is employed. In order to handle uncertainties on human judgments during the evaluation process, the process is conducted under fuzzy environment. Once criteria affecting the decision-making …process of the location of WEEE recycling plant are determined, the Pythagorean fuzzy AHP (PFAHP) method is applied to determine the priority weights of the criteria, sub-criteria and alternative locations. The results of the study show that transportation, recycling, and energy costs are the first three factors respectively, having the highest importance for the selection process, Electric and Electronic Equipment (EEE) usage habits and waste composition are the factors having the least importance. Show more

Keywords: WEEE, recycling, pythagorean fuzzy AHP

DOI: 10.3233/JIFS-179471

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1097-1106, 2020

Authors: Haktanır, Elif

Article Type: Research Article

Abstract:  Hypothesis testing is an important tool of statistical decision making. Classical hypothesis testing is based on a known probability distribution with known population parameters. However, since the data generally include vagueness and impreciseness, a fuzzy set approach should be used. In this paper, interval-valued neutrosophic sets (IVNSs) are used for the purpose of making statistical decisions. In the proposed neutrosophic hypothesis testing approach, neutrosophic linguistic data and neutrosophic parameters are used. Left-sided, right-sided and double-sided neutrosophic hypothesis tests are developed, illustrative example and sensitivity analysis are given.

Keywords: Interval-valued neutrosophic set, hypothesis testing, pythagorean fuzzy sets, hesitant fuzzy sets

DOI: 10.3233/JIFS-179472

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1107-1117, 2020

Authors: Büyüközkan, Gülçin | Güler, Merve

Article Type: Research Article

Abstract: Digital Transformation (DT) is the journey of using digital technologies to develop new business models and strategies. DT aims to achieve competitive advantage and to realize activities that will create efficiency in the corporate value chain. Digital Maturity Model (DMM) provides a practical approach to DT. There is a need for an analytical tool to analyze the significance of the factors in the DMM and to rank the companies according to their digital maturity. It is a multi-criteria decision-making (MCDM) problem with multiple factors under vagueness and impreciseness. Hesitant fuzzy linguistic term sets (HFLTS) is a technique used to facilitate …Decision Makers’ (DMs) judgment process in imprecise situations. HFLTS technique gives DMs possibility to use linguistic expressions with comparative judgments. This article introduces a decision framework based on the HFLTS, Hesitant Fuzzy Linguistic (HFL) Analytic Hierarchy Process (AHP) and HFL Additive Ratio ASsessment (ARAS) methods. It is aimed to provide a scientific method that helps to determine the most important criteria for companies’ DMM and to rank companies. A case study about the banking sector is presented to verify the usability of this method. Show more

Keywords: Digital maturity, hesitant fuzzy linguistic term sets, multi criteria decision making, AHP, ARAS

DOI: 10.3233/JIFS-179473

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 1119-1132, 2020