Journal of Intelligent & Fuzzy Systems - Volume 37, issue 4

Authors: Zhao, Zhongtang | Zhao, Xuezhuan | Li, Lingling

Article Type: Research Article

Abstract: In the field of big data machine learning, the data volume is large, but the labeled data is few. Due to this, it may lead to that the distribution of labeled data (source domain) is not similar to that of unlabeled data (target domain). In traditional machine learning field, this problem is a kind of transfer learning problems. To address this problem, a self labeling online sequential extreme learning machine is presented, which is called SLOSELM. Firstly, an ELM classifier is trained on the labeled training dataset of the source domain. Secondly, the unlabelled dataset of the target domain is …classified by the ELM classifier. In the third step, the high confident samples are selected and the OSELM is employed to update the original ELM classifier. Tested on the real-world image dataset and the daily activity dataset, the results show that our algorithm performs well. Show more

Keywords: Extreme learning machine, activity recognition, transfer learning, big data, pervasive computing

DOI: 10.3233/JIFS-179281

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4485-4491, 2019

Authors: Zhao, Hongwei | Liu, Yuqi | Huang, Yongping | Lu, Xuwang | Tu, Xiaohang

Article Type: Research Article

Abstract: Aiming at the problem of low prediction accuracy and slow training time for Neural network with single hidden layer forecast, this paper proposes a combination of Multitask and DBN Neural network used to predict the short-term free parking berths. Firstly, the DBN Neural Network is used to carry out auto correlation analysis of the original data, and the characteristics of the data inclusion are obtained. Combined with Multitask Learning, the paper studies several related tasks simultaneously, the Neural Network can have the knowledge to new things for forecasting, and compared with the existing Neural network with single hidden layer, the …data preprocessing process is reduced and better prediction results are obtained. The results show that this method shortens the training time and improves the prediction results. Show more

Keywords: Free parking berths, multitask learning, DBN neural network

DOI: 10.3233/JIFS-179282

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4493-4498, 2019

Authors: Zhang, Yongli | Han, Tailin | Lang, Baihe | Li, Yang | Lai, Fuwen

Article Type: Research Article

Abstract: The shockwave signal is affected by the weapon launch and the external environment, and it is often mixed with many kinds of noise, some even submerged. To detect and extract the shockwave signal under low signal-to-noise ratio, the transient signal SNR, the power-law detector of the higher-order cumulant spectrum (HOCS) and the Dual-tree complex wavelet transform (DTCWT) extraction model are proposed in the study. The average power of noise under different SNR was calculated by comparing the average power of the background noise with the instantaneous power of the shockwave. Based on the power-law detection of HOCS, the power-law of …the two spectra was analyzed. After the DTCWT, the optimal threshold of the maximum posterior estimation was denoted by layer by layer, then the shockwave signal was extracted by the inverse transform, and the validity of the model was verified by the measured data. Results demonstrate that the signal to noise ratio of the transient signal can reflect the true magnitude of the average power of the noise, and the conventional SNR reduces the average power of the noise, and the error ratio is up to 70%. The power-law detector of bispectrum diagonals has the good effect on Gaussian white noise suppression, and can detect the signal to noise ratio of -15dB. The DTCWT can realize multiple peak shockwave extraction with the smaller amplitude, and the mean square error (MSE) of measured signal extraction can reach 0.0189. The proposed method provides a good reference for the detection of shockwave signal and the extraction of the multi-peak waveform in low signal-to-noise ratio. Show more

Keywords: Shockwave, power-law detector, high order spectral transform, dual-tree complex wavelet transform

DOI: 10.3233/JIFS-179283

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4499-4510, 2019

Authors: Ding, Xiaobing | Liu, Zhigang | Hu, Hua | Huang, Yuanchun | Yu, Jie

Article Type: Research Article

Abstract: In this work, we proposed a new systematic metro operation risk identification method (MORIM) and risk grade classification method (RGLM) based on the daily dispatching fault log. We collected and analysed the operation risks during Metro operation, and the database SQL was designed for calculating the probability of risks. Then, we converted the equipment malfunction, train delay, large passenger flow etc. to time delay, so as to realize the quantitative calculation of the risks. We clustered risk sources by data mining, from which, we can get the risk cluster centre, and the emergency response scheme can be accurately made to …match the clustered risks. Finally, the systematic method was validated by a case study. It was found that the method was accurate and the conclusion was reliable. This paper can provide theory and decision support for Metro operation safety management and it has good practical significance for larger cities to dispose the conditions of large passenger flow. Show more

Keywords: Intelligent identification algorithm, fault log, data mining, operation risks, urban rail transportation

DOI: 10.3233/JIFS-179284

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4511-4522, 2019

Authors: Zhou, Weifeng | Hou, Juan | Fan, Wei | Dai, Yang

Article Type: Research Article

Abstract: In this study, we develop a kind of location-based marine fishery information service method. The method is to use position and communication function of BeiDou navigation satellite system and shipborne marine environment monitoring sensors to obtain the location information, production data and marine environment data measured in situ, and then to extract the grid data around the target fishing vessel and transform these data into environment data in the form of vector. Then information service center takes the production data and environment data measured in situ as training sample to optimize the set fishing ground forecast model in accuracy and …generalization. The model is used to calculate the fishing ground probability around the target fishing vessel. Finally, the information service center encodes the result of the forecast and related environment information together and send them to the target vessel. The method providing a location-based, vessel-oriented, customized and high-precision service, data generated from which is far less than those from some traditional methods, is cost-effective and easy to be popularized and applied by fishery operation departments. Show more

Keywords: Marine fishery, information service, satellite navigation communication system, fishing ground forecasting

DOI: 10.3233/JIFS-179285

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4523-4530, 2019

Authors: Ji, Wenjiang | Zhu, Lei | Wang, Yichuan | Liu, Zheng | Hei, Xinhong

Article Type: Research Article

Abstract: Vehicular ad hoc networks (VANET) is seen as an effective solution to ensure the driving safety and efficiency. As a key foundation, the road side unit (RSU) connect with each other to form a backbone network in VANET. The authentication of RSUs is the main tasks to prevent the secure communication in VANET suffering from various attacks caused by cunning adversaries. In this paper, we propose a new type of verifiable secret sharing (VSS) scheme based on bivariate polynomial to achieving the RSU authentication in a secret sharing way. Our proposed VSS based authentication includes two phases. In phase 1, …the t RSUs that participate in secret reconstruction collaborate to detect whether there exist illegitimate ones; in phase 2, the t legitimate RSUs reveal their shares for secret reconstruction, and the fake shares can be identified. Our VSS facilitates the RSU authentication since (1) any RSUs participate in secret reconstruction can be confirmed legitimate, (2) any fake shares revealed in secret reconstruction can be identified, (3) a globalized group temporary session key will be established after the VSS process. In addition, our VSS scheme is unconditional secure since the security of our VSS is not based on any computational assumption. Show more

Keywords: Vehicular ad hoc networks, security, RSU authentication, verifiable secret sharing

DOI: 10.3233/JIFS-179286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4531-4536, 2019

Authors: Cao, Yan | Wei, Wanyu | Huang, Liang | Qiao, Hu | Du, Jiang

Article Type: Research Article

Abstract: Uncertain sporadic risks have prominent features such as small probability, difficult to predict, fast diffusion, and complex types, which greatly increase the difficulty of control. Severe incidental risk events often affect the normal operation of the supply chain system, so it is particularly important to respond to risks in a timely and effective manner. Based on fuzzy logic, this paper studies the coping strategies of three-level supply chain systems composed of manufacturers, distribution centers and retailers under uncertain risks. Firstly, fuzzy logic is used to highly quantify fuzzy variables to calculate specific changes caused by the uncertain risks to members …in supply chain, and effectively predict overall changes of the supply chain system; Secondly, the member information is updated in the post-change supply chain system. On this basis, the member maximum loss model is established, the maximum loss amount and the amount of each strategy loss are calculated, and a risk response strategy plan is formulated. Finally, a coping strategy is stored for a quick call when similar risks occur again. The feasibility and effectiveness of the model and method are verified by specific examples and variable sensitivity analysis. Show more

Keywords: Manufacturing supply chain, risk response, maximum loss, decision analysis, fuzzy logic

DOI: 10.3233/JIFS-179287

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4537-4546, 2019

Authors: Wei, Xinyuan | Zang, Hongyan

Article Type: Research Article

Abstract: This paper proposes two kind of new cubic chaotic maps based on Li-Yorke’s chaos criterion theorem, and gives the corresponding chaos discriminant conditions. The dynamical behaviors of systems are numerically simulated by nonlinear techniques including bifurcation diagrams and Laypunov exponents, and the simulation results show the cubic chaotic maps display chaotic characteristics as the provided theorems expect. Using spectral entropy algorithm, this paper analyses the complexity of chaotic sequences generated by cubic chaotic maps after quantitative process, and further compares the complexity of the chaotic pseudorandom sequences based on different quantitative methods. The results show different quantitative methods has a …significant effect on the complexity of chaotic sequences; the pseudorandom sequences generated by the systems and quantitative method provided in this paper turns to have a better complexity. The above conclusions provide a theoretical basis for generating pseudorandom sequences with better quality. Show more

Keywords: Cubic chaotic maps, lyapunov exponent, spectral entropy, complexity

DOI: 10.3233/JIFS-179288

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4547-4555, 2019

Authors: Yi, Haibo

Article Type: Research Article

Abstract: Over the past few years, there has been a sustaining interest in research of secure communication architectures and protocols based on asymmetric cryptographic techniques. However, it is showed that quantum computers can break most asymmetric cryptographic techniques and they will be insecure. In this paper, we focus on accelerating quantum-safe cryptography for communication systems by improving inversions in finite fields. Cellular Automaton (CA) is a discrete model in mathematics, physics, computer science and neural computing. It is a grid of cells with a finite number of states and it has been adopted and applied to many research and engineering fields, …e.g., cryptography and neural computing. In addition, cellular automata can simulate many real-world systems, such as biological system, Vehicular Communication (VC) systems and neural networks. We propose a variant of Fermat’s theorem inversion based on cellular automaton. We implement inversions in finite fields on Application Specific Integrated Circuit (ASIC) and accelerate some quantum-safe signature schemes, which shows that they are efficient for constructing quantum-safe communications. Show more

Keywords: Cellular automaton (CA), inversions, neural network

DOI: 10.3233/JIFS-179289

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4557-4562, 2019

Authors: Wang, Shu | Yu, Qiang | Zhao, Xuan | Zhang, Shuo | Ye, Yiming

Article Type: Research Article

Abstract: Vehicle sideslip angle is the key parameter to evaluate the handling stability of the vehicle, and it is also one of the control targets of the vehicle stability, so the accurate estimation of the vehicle sideslip angle directly affects the safety of the vehicle. In order to improve the influence of particles degeneracy on the estimation of vehicle sideslip angle, and ensure the nonnegative qualitative of the covariance matrix and iterative stability of the unscented Kalman filter algorithm, in this paper, a vehicle sideslip angle estimation method based on singular value decomposition Unscented Kalman particle filtering algorithm (SVD-UPF) is proposed …by using two-degrees-of-freedom nonlinear vehicle dynamics model, and the singular value decomposition Unscented Kalman filter algorithm is used to optimize the density distribution function. Using the hardware-in-the-loop simulation platform of distributed drive electric vehicle (HEV), the method of estimating the vehicle sideslip angle based on the unscented Kalman filter(UKF) and the SVD-UPF algorithm is compared and verified under the working condition of emergency double lane change, steering angle increase gradually, steering wheel angle stepping. The results show that the SVD-UPF estimator improves the accuracy of the unscented Kalman filter estimator and the effectiveness of the algorithm is verified. Show more

Keywords: Sideslip angle estimation, singular value decomposition, unscented kalman particle filter algorithm, accuracy

DOI: 10.3233/JIFS-179290

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4563-4573, 2019

Authors: Yi, Haibo | Chi, Ruinan | Nie, Zhe

Article Type: Research Article

Abstract: There has been a continuous and increasing interest in research and application of Wireless Sensor Networks (WSNs). Although the future of WSNs is very prospective, the security issues become more and more important because they are used for very critical applications in engineering areas. Furthermore, they are very vulnerable and thus attractive to attacks because of human-unattended deployment and their limited prices. Generally, they are protected by public key cryptosystems. Such systems depends on the difficulty of the elliptic curve discrete logarithms or integer factorizations. However, they can be attacked by Shor’s algorithm on quantum computers. Multivariate Public Key Cryptography …(MPKC) schemes are secure to attacks by quantum computers. Among such schemes, multivariate signatures use various multiplications in a finite field, which are time-consuming operations during signature generations. Thus, we focus on improving multiplications in finite fields for multivariate signatures. We propose a variant of Mastrovito multiplications based on trinomial, Special Trinomial (ST), pentanomial, Special Pentanomial (SP), Equally-spaced-polynomial (ESP), All-One-polynomial (AOP), and successive-one-polynomial (SOP). Our design is implemented on hardware and can be used to improve the implementations of multivariate signatures including UOV, enTTS and Rainbow for protecting data security in WSNs. Show more

Keywords: Multiplication, finite field, wireless sensor networks (WSNs), multivariate signature

DOI: 10.3233/JIFS-179291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4575-4584, 2019

Authors: Xie, Qubo | Zhou, Ke | Fu, Xiao | Fan, Xiaohu

Article Type: Research Article

Abstract: Recently, many breakthroughs have been achieved in the text detection field; however, printed text detection performance remains unsatisfactory. To address this issue, this paper proposes a refined feature attention based text detection model comprising a feature attention FCNs and text instance segmentation. With the feature attention mechanism, the FCNs model is optimized effectively, which enables the network to learn more precise and accurate features. Therefore, the network can better detect noise-intensive and dense text in medical images. In addition, a centerline-based text region detection algorithm is proposed to process the output of network during text instance segmentation. This algorithm calculates …each text region according to the geometric information of the text instance; thus, it is able to process multi-oriented text instances precisely. The proposed model can be trained end-to-end and does not require post-processing operations, which greatly increases detection efficiency. The proposed model achieved excellent results on a medical text image dataset. Compared to existing text detection models, the proposed model demonstrates significantly better performance in terms of F-meatures and detection speed. Show more

Keywords: Printed text detection, attention mechanism, medical text image, image instance segmentation

DOI: 10.3233/JIFS-179292

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4585-4594, 2019

Authors: Hu, Zhiqiang | Yuan, Xiaoping

Article Type: Research Article

Abstract: A key radiation sources during the laser-cutting process is sparks, the spark jet angle is closely related to the quality of laser-cutting. A new approach to extract the angle of laser-cut spark jets in industrial metal-cutting processes is presented based on an established machine vision platform. This research demonstrated the algorithm and key theory of PCA and its use in image-processing. The laser-cutting experiment carried out on an St12 steel, the spark images captured during real-time operation are analysed by using the proposed algorithm to obtain the angle and shape of spark jets: the cutting kerf is analysed by optical …microscope to acquire the kerf width and associated features. The quantifiable link between sparks angle and kerf width is testified by tests on 1.8-mm thick St12 steel plate, and the results conform to the rules associated with the laser-cutting of metal. Show more

Keywords: Computer vision, laser-cutting, spark jet angle, quality analysis, PCA

DOI: 10.3233/JIFS-179293

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4595-4603, 2019

Authors: Yin, Xiaoqi | Qian, Jiansheng | Guo, Xingge | Fu, Chengfang | Lin, Guohua

Article Type: Research Article

Abstract: Measurement matrix is an important link which has important influence on signal sampling and reconstruction algorithm. Although the traditional random measurement matrix has good effect in reconstruction signal, the hardware implementation is difficult and it requires a lot of storage space. LDPC codes has a sparse check matrix with low density and strong orthogonality. When the RIP conditions are satisfied, the columns and rows are not correlated. In view of the problems existing in the measurement matrix, the deterministic measurement matrix based on the sparsity of photograph LDPC codes is constructed in this paper. Each submatrix is obtained through the …circular shift of other submatrices, which is easy to be implemented on hardware. Experimental results show that the sparse matrix performance of LDPC codes is improved in PSNR and dNMSE compared to the traditional methods by using the same orthogonal matching pursuit (OMP) algorithm for optimization and the same compression ratio. At the same time, it consumes less time in the reconstruction of remote sensing image, and the running speed is greatly improved, which can meet the real-time demand, it also provides an effective measurement matrix construction method for the practical application of compressed sensing theory. Show more

Keywords: Compressed sensing, sparse matrix, LDPC, photograph, orthogonal matching pursuit, wavelet transform

DOI: 10.3233/JIFS-179294

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4605-4613, 2019

Authors: Zhang, Yueling | Pu, Geguang | Zhang, Min | Y, William

Article Type: Research Article

Abstract: Deep Neural Network is an application of Big Data, and the robustness of Big Data is one of the most important issues. This paper proposes a new approach named PCD for computing adversarial examples for Deep Neural Network (DNN) and increase the robustness of Big Data. In safety-critical applications, adversarial examples are big threats to the reliability of DNNs. PCD generates adversarial examples by generating different coverage of pooling functions using gradient ascent. Among the 2707 input images, PCD generates 672 adversarial examples with L ∞ distances less than 0.3. Comparing to PGD (state-of-art tool for generating adversarial examples …with distances less than 0.3), PCD finds 1.5 times more adversarial examples than PGD (449) does. Show more

Keywords: Deep neural network, robustness, coverage, big data

DOI: 10.3233/JIFS-179295

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4615-4620, 2019

Authors: Lin, Yu | Yu, Xuejun | Glaubitt, Walther

Article Type: Research Article

Abstract: At present, distributed systems have been widely used, and a lot of research has been done on the reliability of distributed systems. However, trusted 3.0 based distributed system node trust behavior recognition research is still relatively rare. This paper focuses on the identification process and evaluation method of distributed node trust behavior. In this paper, call links and resource consumption of software behavior are obtained by burying points during the development phase. Based on the idea of “sense of words and deeds”, this paper compares the pre-acquired trust call links with the resource consumption sample data, in order to obtain …a credible real-time software behavior model. This paper will focus on the analysis and extend to the distributed environment, and conduct a trusted analysis of software behavior, which provides a new idea for software trusted behavior analysis. Show more

Keywords: Trust 3.0, distributed nodes, trusted behavior, identification model

DOI: 10.3233/JIFS-179296

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4621-4631, 2019

Authors: Li, Yan

Article Type: Research Article

Abstract: As the main tool to monitor remote networking environment, sensor network integrates various functions of data collection, data collection, data processing and information transmission information data encryption in one, which has been gradually applied in all areas of society. However, sensor networks may suffer attacks during the process of data acquisition and transmission. Therefore, data privacy protection becomes the most important problem in wireless sensor networks. In this paper, privacy protection, high precision and data fusion were studied, and a privacy preserving algorithm based on CRAE was proposed on the existing encryption algorithms. The algorithm can not only reduce the …energy consumption of sensor networks, but also have good privacy. Simulation experiments were carried out to compare the proposed algorithm with the existing encryption algorithms and achieve the desired design goal. Show more

Keywords: Privacy protection, sensor networks, data fusion, energy consumption

DOI: 10.3233/JIFS-179297

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4633-4638, 2019

Authors: Li, Yan

Article Type: Research Article

Abstract: With the development and wide application of wireless sensor networks, a data detection method based on time series is proposed to solve the problem that the sampling values of sensors vary greatly in harsh environments and the detection results of events are inaccurate with the increase of fault nodes in wireless sensor networks. The median of the normal data collected by the sensor is used to establish the reference value, and then the confidence interval is constructed. Finally, a method based on calculating the difference degree of the data interval is proposed to determine the source of the anomaly. The …experimental results show that the proposed method keeps the detection rate of abnormal data in sensor networks above 98% and the false alarm rate below 0.6%. It has certain reliability and practicability. Show more

Keywords: Anomaly detection, wireless sensor network, data buffer, confidence interval, difference

DOI: 10.3233/JIFS-179298

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4639-4645, 2019

Authors: ZHOU, Zhou | Xie, Houliang | Li, Fangmin

Article Type: Research Article

Abstract: To deal with the problem of unbalanced load and ignoring task priority in previous task scheduling algorithms, this paper proposes a task scheduling algorithm named P-Min-Min-Max, which combines with priority and greedy strategy. Under the condition of considering the task priority, the algorithm leverages the execution time of tasks for greedy strategy, and binding large task and small task in the task list to form “task pair” to perform scheduling, so as to effectively solve the problem of unbalanced load. To reduce the average response time of tasks, the algorithm priority schedules the small task from the “task pair”. The …experimental results show that, compared with the Min-Min and P-Min-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and saves the total execution time for tasks. Compared with Max-Min and P-Max-Min algorithm, the proposed algorithm improves the system resource utilization and service quality of user, and reduces the total completion time and average response time. Show more

Keywords: Cloud computing, greedy strategy, load balancing, priority, service quality

DOI: 10.3233/JIFS-179299

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4647-4655, 2019

Authors: Cui, Le | Cheng, Libo | Jiang, Xiaoming | Chen, Zhanfang | Albarka,

Article Type: Research Article

Abstract: Outlier detection has always been a more active research topic in statistical diagnosis. Outliers are ubiquitous at data analysis areas in current and may produce erroneous results. In multivariate linear regression model, the existence of outliers will directly affect the modeling, parameter estimation and prediction. A set of data contains abnormal values, which will have a great impact on the estimation of the mean and standard deviation of the data, and also affect the estimation results of the least squares method. In the paper, on the basis of the linear regression model and deleting model and mean shift model, from …the perspective of residual sum of squares and by introducing sample quantile to estimate the overall parameters robustly, a special statistic which is combined with the sample quantile method is used to detected the outliers. Finally, an example is analyzed and compared with the traditional method. The results show that the method is more effective. Show more

Keywords: Regression analysis, outlier, data deletion model, mean shift model, residual sum of squares, sample quantile

DOI: 10.3233/JIFS-179300

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4657-4664, 2019

Authors: Lu, Hsin-Ke | Lin, Peng-Chun | Chu, Kuo-Chung | Chen, Alexander N. | Yuan, An

Article Type: Research Article

Abstract: According to the reports of a NGO-World Blind Union in 2017, approximately 253 million people have visual impairment. Besides, the statistics of Taiwan’s Ministry of Health and Welfare also reported that the number keep growing in these two decades. Therefore, how to assist them to have better daily life experiences will be a significant issue. The purposes of this study were designing and constructing a guidance system in order to assist them to know their spatial position and further to guide them to arrive their destination. In this system, the researchers used the integration of smartphone, wearable devices and iBeacon …technique to achieve the purpose of guide. Furthermore, this system allowed caregivers to contact the visually impaired and know their real-time circumstances through the internet in order to enhance their sense of security in unfamiliar indoor environment. For system evaluation, the researchers adopted a SUMI questionnaire suitable for evaluating the usability of the system through users’ feedbacks. According to the research survey, this system can provide the visually impaired with a safer indoor guidance in order to improve their ability and confidence in independent walking. Show more

Keywords: Visual impairment, indoor positioning, Beacon, navigation

DOI: 10.3233/JIFS-179301

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4665-4675, 2019

Authors: Li, Yu | Yuan, Kun | Cai, Qian | Yu, Fengyuan | Cai, Chengfeng | Li, Xiaoying | Liu, Pengfeng | Qian, Meiyu | Yu, Juan | Peng, Xiaomei | Chen, Hongguan | Qin, Runtian | Wang, Ziwei | Huang, Nanxi | Liu, Kongling | Cheng, Zhi

Article Type: Research Article

Abstract: People can rely on complex tactile systems to perceive the basic physical properties of an object, and take the corresponding action and pressure to grab the object. However, this task is not easy for mechanical manipulator. The feedback of most manipulators is limited to pressure, it is difficult for manipulators to identify the other properties of the object by touch. A new manipulator method is designed in this paper. The tactile images are reflected by flexible tactile sensor in this manipulator system. A large number of tactile images are used to build training set by which the capsule network is …trained to evaluate images. When an object is captured by a manipulator, and parameters such as shape, rigidity, weight and density of target objects are analyzed. Pseudo color transformation of tactile images is performed, in this way, the changes of each parameter of tactile signals can be observed visibly. It is innovative to process the tactile image by using capsule network and realize the evolutionary bionic tactile function. Show more

Keywords: Capsule network, image processing, bionic manipulator, pseudo color image

DOI: 10.3233/JIFS-179302

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4677-4685, 2019

Authors: Yao, Fuguang

Article Type: Research Article

Abstract: At present, China has great difficulty in obtaining the reliability of teaching data sources. In order to further improve the effectiveness of data mining and reduce the difficulty of data acquisition, this paper studies the design and simulation of integrated education information teaching system based on fuzzy logic. Bayesian algorithm can perform data mining, feature recognition and classification on data in big data, so that it can effectively process massive data sources. By weighting the different network structures, the number of undirected edges in the network is reduced, and then small data sets that can be processed by multiple traditional …algorithms are sampled from the big data set, and data is generated by using the Bayesian network toolkit Samiam. The modules respectively generate data sets of different sizes and construct a teaching data source generation model. The experimental results show that RSEM on Child and Alarm data can take less time and achieve an accuracy of 86.17% compared with the whole data set under the same effect. This paper proposes a Bayesian network structure integration model, which can solve the problem of data acquisition difficulties, and is also a further improvement of data mining technology. Show more

Keywords: Deep learning, data mining, teaching data source

DOI: 10.3233/JIFS-179303

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4687-4695, 2019

Authors: Chen, Limin | Ma, Mengli | Sun, Lixin

Article Type: Research Article

Abstract:  In the current agricultural product consumption market, the consumer’s demand for agricultural products tends to be diversified and individualized, and they need stricter links of cold chain logistics distribution of agricultural products. The cold chain logistics of fresh agricultural products is also the business of high energy consumption and high carbon emission in the logistics industry. The contradictory relationship between it and the “low-carbon economy” advocated today leads to the necessity to consider the relationship between economic benefit and environmental impact in the process of rapid development. Based on this, this paper, from the perspective of low-carbon economy, based on …the analysis of the necessity of optimizing the distribution path of cold chain logistics of agricultural products, constructs a model for this and puts forward a swarm intelligence optimization algorithm-particle swarm optimization (PSO) algorithm. The algorithm is improved from inertia weight, convergence factor, learning factor, and population size and so on. The optimized PSO algorithm is compared with the traditional PSO algorithm. Finally, the simulation results show that the improved algorithm can be used to optimize the distribution path of cold chain logistics of agricultural products effectively, and the specific optimization countermeasures are put forward according to the actual situation. Show more

Keywords: Low carbon economy, cold chain logistics, agricultural products, distribution system, optimization

DOI: 10.3233/JIFS-179304

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4697-4703, 2019

Authors: Liu, Yi | Lu, Jiahuan | Mao, Feng | Tong, Kaidi

Article Type: Research Article

Abstract: In order to pre-warning the product quality risk of the e-commerce platform, this paper studies the machine learning algorithm for the products quality risk assessment, which propose the Fuzzy C-Means clustering algorithm for the feature extraction and the Cost Sensitive Leaning (CSL)-Naive Bayesian algorithm to construct the assessment model for E-commerce product quality risk form the massive and unbalanced data. The experimental results show that the Machine Learning algorithm based on Spark has better scalability and superiority in the large-scale data environment, which can accurately identify e-commerce product quality risk.

Keywords: E-commerce product quality, risk assessment, fuzzy c-means clustering algorithm, cost sensitive leaning, Naive Bayesian algorithm

DOI: 10.3233/JIFS-179305

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4705-4715, 2019

Authors: Mao, Jia | Liu, Ruiping | Zhang, Xiuzhi

Article Type: Research Article

Abstract: There are many optional basic frameworks of the Internet of Things, which result in high energy consumption for Internet of Things monitoring platform of straw recycling, and cannot improve the thermal energy conversion rate of the straw recycling monitoring system effectively. Thus, the design is based on smart surveillance system of Internet of things of straw recycling process. The WMNBM14s chip and the STM32F103 chip are used in the basic frame of Internet of things to collect and process the straw recycling data in the monitoring system, and obtain the data processing result of the straw recycling process. The data …processing result of the straw recycling process is transmitted to Internet of Things Control Terminal through the BCM43362 wireless chip. The experimental results show that the designed platform has low energy consumption and can improve the thermal energy conversion rate of the straw recovery system. Show more

Keywords: Genetic algorithm, straw recycling process, Internet of Things monitoring system, BCM43362

DOI: 10.3233/JIFS-179306

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4717-4723, 2019

Authors: Wei, Pengcheng | Li, Li

Article Type: Research Article

Abstract: How to recommend learning resources to users accurately to meet the individual needs of users becomes the key issue with the increasing number of online education users. A personalized recommendation system was proposed in this paper based on user preference behavior data analysis to analyze the online education recommendation model. It determines the criteria set of the recommendation system with the product attribute mining method, and then uses the personalized recommendation algorithm for user preference modeling to explore the user’s preference for each criterion, thereby producing more accurate recommendations. The simulation results of the algorithm proposed in this paper show …that the multi-criteria recommendation algorithm using user distance similarity works best. Using this personalized recommendation algorithm based on user preference can effectively improve the recommendation quality. Show more

Keywords: User behavior, data analysis, online education

DOI: 10.3233/JIFS-179307

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4725-4733, 2019

Authors: Wen, Li-Hua | Shi, Zhi-Hua | Liu, Hong-Yao

Article Type: Research Article

Abstract: There are various kinds of common natural disasters, including flood, drought, typhoon, geological disaster, forest fire and major biological disaster. Natural disaster is an abnormal event in the evolution of geographical environment, but it has become one of the most important natural factors hindering the development of human society. With the economic development and population expansion of human beings, water resource shortage is becoming more and more serious, so drought has always been a major natural disaster faced by mankind. This paper studies the GIS-based risk assessment and regionalization of Taihang Mountain drought and flood disasters. In the process of …regional environmental quality assessment, GIS technology is used to conduct an objective and comprehensive evaluation of the environmental quality of the whole region. This paper then constructs the combination of GIS technology and QUEST algorithm. Based on the decision tree model of Taihang Mountain drought disaster risk assessment, the risk of drought disaster in Taihang Mountain is evaluated. The results show that the distribution of drought disaster in Taihang Mountains is similar to that of drought disaster risk. The risk of drought disaster mainly distributes in the middle and west of Taihang Mountains. The risk in the east of Taihang Mountains is the lowest. The risk in the west of Taihang Mountains increases gradually. Generally speaking, the drought resistance of southern Taihang Mountains is higher than that of northern Taihang Mountains. Show more

Keywords: GIS, Taihang Mountain, drought disaster, risk assessment, zoning

DOI: 10.3233/JIFS-179308

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4735-4743, 2019

Authors: Yan, Shuhua | Guo, Linfeng

Article Type: Research Article

Abstract: Stock market trading is relatively difficult due to the relatively complicated investment in financial markets. In order to solve this problem, an industry configuration model based on deep learning network sentiment mining and fundamental research is proposed innovatively in this paper. Firstly, by crawling the network information, the network public opinion data is used to conduct industry classification and sentiment analysis on the data, thereby obtaining the industry sentiment index and the industry income forecast. Then combined with the fundamental data and market data and the technical indicators generated by it, multi-factor analysis is carried out, and the income forecast …is obtained. Through three sets of comparative experiments, the results show that the investment returns obtained are the best with the industry configuration model based on deep learning-based network sentiment mining and fundamental research. Show more

Keywords: Recurrent neural network, internet emotion mining, word vector analysis, industry configuration, fundamental analysis

DOI: 10.3233/JIFS-179309

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4745-4752, 2019

Authors: Yang, Ming

Article Type: Research Article

Abstract:  There are still many problems in the application of face recognition technology in specific environments. In order to improve the recognition accuracy of face recognition technology in large-scale event scenes, a face tracking algorithm is constructed based on improved ORB features in this paper. The algorithm uses the kernel function color histogram to model the target, which can perform well on target recognition during rotation or edge occlusion. The value of the face representation function is calculated by combining the texture feature and the color feature. By converting the function value into moment feature and combining it with the Bhattacharyya …coefficient, the tracking performance of the target and the accurate detection of the target real scale improves. Taking the Tianjin National Games as an example, the intelligent security system based on face recognition was designed and implemented. The test results show that the proposed algorithm can reduce the face feature dimension effectively. When the control library is no more than 10,000 people, the false alarm rate is 1%, and the false negative rate is less than 5%. It provides a new recognition method for face recognition in the application of large-scale event scenes. Show more

Keywords: Face recognition, active scene, face tracking algorithm

DOI: 10.3233/JIFS-179310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4753-4761, 2019

Authors: Yang, Yanguo | Yu, Jiaqi | Fu, Yubin | Hu, Jiangtao

Article Type: Research Article

Abstract: As there are many uncertain factors in the geological hazard risk, great challenges are brought to the comprehensive evaluation of it. In order to improve the comprehensiveness and accuracy of geological hazard risk assessment, a cloud fuzzy clustering algorithm is constructed in this paper, which can effectively estimate and evaluate uncertain variables. The weight value of the risk cloud droplets is calculated as the input. By setting up clustering conditions and function output conditions, the cluster weights of the inputs which meet requirements can be obtained by multiple clustering iterations. Through the introduction of time parameters, the influence of time …factors on data importance and the risk severity of geological disaster emergencies are fully considered. The experimental results show that the calculated risk degree cluster weights are less than 1, which verifies the feasibility and practicability of the algorithm. The research in this paper shows that the clustering dynamic assessment of geological hazards can help to improve the accuracy of risk assessment and provide reference and help for the prevention and control of regional geological hazards. Show more

Keywords: Fuzzy, clustering algorithm, geological hazards

DOI: 10.3233/JIFS-179311

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4763-4770, 2019

Authors: Guo, Xiaoyu | Zhou, Jing | Wang, Xi

Article Type: Research Article

Abstract: The efficiency of the supply chain of pig breeding in China is low due to the structure of scattering raising-households and the competition among the enterprises within the supply chain is also fierce. Faced with the uncertainty of the market environment and the complexity of the decision-making environment, how to choose the competitive strategy and competition mode for pig breeding enterprises and determine the optimal sales price and sales volume is the key problem to be solved by enterprises in the supply chain management. Based on this, this paper constructs a model of competition between two manufacturers (large farmers) and …two retailers (pork wholesalers) in the pig breeding industry under fuzzy environment. Under the three modes of Cournot competition, Collusion competition and Stackelberg competition, the competition model between two retailers is constructed in turn, and the optimal strategy of each manufacturer and retailer is obtained. Finally, the mental state index is introduced to describe the decision maker’s attitude or preference to the risk, which can make the model more reasonable. The result shows that the change of the mental state index will not only influence the optimal solution, but also affect the final decision result. Show more

Keywords: Game theory, supply chain, Cournot competition, stackelberg competition, fuzzy number

DOI: 10.3233/JIFS-179312

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4771-4778, 2019

Authors: Cui, Ranran

Article Type: Research Article

Abstract: We shall consider intelligent homological dimensions of 0-direct union of finite Rees matrix semigroups. First we give some characterizations of Rees matrix semigroup algebras. Then if K is a ring and S has a Rees matrix ideal M, we give the bounds of r.gl.dim K[S] in terms of r.gl.dim K  [T i ] and r.gl.dim K[S/M]. The bounds for r.gl.dim K[S] are given, supposing that the finite monoid S is a 0-direct union of some finite Rees matrix semigroups which are in forms of S i  = M (T i  ; I i  ; Λ i  ; P i ). …In addition, it is determined that K[S] has finite homological dimension if and only if each T i has finite homological dimension. Show more

Keywords: Homological dimension, *-ideal chain, primitively decomposable abundant semigroups, inverse semigroup, intelligent

DOI: 10.3233/JIFS-179313

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4779-4783, 2019

Authors: Wu, Yongfen

Article Type: Research Article

Abstract: This paper reprocesses the information of the boundary intelligent contour so as to effectively extract the codes of image contour features. The algorithm based on the coordinates of contour extracted through the level set evolution algorithm is used to obtain several 2D contour matrixes with the same size after repeated conversions. Moreover, the matrixes are diagonally, column-wise and horizontally coded to obtain new coded features. The anti-interference analysis of algorithm indicates that the algorithm of extracting feature code has variable and flexible extraction schemes and high stability. Distinguishable information can be obtained in similar images more easily. In order to …prove the validity of the proposed algorithm, feature code exaction algorithm is used to facial expression recognition, and a facial expression recognition model on the basis of facial part contour code exaction is established. According to the experimental results, this facial expression recognition system can eliminate the interference with recognition resulted from the similarity of samples. The comprehensive recognition rate of facial expression is up to 97.20%. Show more

Keywords: Image contour, feature extraction, feature code, image recognition, intelligent

DOI: 10.3233/JIFS-179314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4785-4795, 2019

Authors: Shen, Chen | Lin, Hongfei | Hao, Huihui | Yang, Zhihao | Wang, Jian | Zhang, Shaowu

Article Type: Research Article

Abstract: With the rapid development of clinical and laboratory medicine, the field of bioinformatics boasts of extensive clinical records and research literature. Retrieving effective information from this huge data has become a challenging task. Hence, Intelligent text summarization, which enables users to find and understand relevant source texts more quickly and effortlessly, becomes a very significant and valuable field of research. In this study, we propose an improved TextRank algorithm with weight calculation based on sentence graph to solve this problem. For the experimental dataset obtained from Pubmed, we represent terms as vectors by using Skip-gram model. We design three methods …which utilize word embeddings to calculate weights between sentences. Then we build an undirected graph with sentences as nodes. At last, we use the improved TextRank algorithm to calculate the importance of sentences and further generated summarizations base on its ranking. The experimental results and analysis on the datasets demonstrate the effectiveness of the proposed model. Show more

Keywords: Intelligent, text summarization, graph-based ranking, similarity calculation

DOI: 10.3233/JIFS-179315

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4797-4802, 2019

Authors: Pang, Hui | Dong, Shaohua | Zhang, Xinwei

Article Type: Research Article

Abstract: In this paper, under the circumstance of uncertain customer demand, the enterprises on the same node in multiple supply chains conduct horizontal inventory coordination according to their own inventory and demand. Based on the combination of horizontal inventory replenishment and vertical normal replenishment, the related mathematical model has been established. By studying the inventory strategy in the decentralized and centralized decision-making, the dual marginalization effects are found in the network system composed of multiple supply chain. So the revenue sharing contract is introduced to solve this problem. It has been found in the study that after adopting the horizontal inventory …coordination mechanism of the supply chain, the profit of the members in the supply chain system and the overall profit of the system are both higher than those which didn’t adopt the mechanism. The improved multi-objective genetic algorithm is used to calculate and verify the problem. In particular, after the revenue sharing contract is adopted, the profits are further enhanced. Show more

Keywords: Inventory coordination, economic order quantity, inventory strategy, revenue sharing, multi-objective genetic algorithm

DOI: 10.3233/JIFS-179316

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4803-4810, 2019

Authors: Luo, Junhui | Liu, Xianlin | Mi, Decai | Chen, Deqiang | He, Zhifen | Xu, Longwang

Article Type: Research Article

Abstract: In Guangxi marine soft foundation of a highway, the research of the intelligent dynamic response of marine roadbeds under traffic loading is carried out. To describe the interaction characteristics of vehicles and soft marine foundation, fine-analyzing the mechanical mechanism of various kinds of damage in early stage and the key factors affecting on the car, it need step up pavement coupling. Accordingly, it was based on the assumption of rigid pavement based on the Lagrange method, meet the viscoelastic foundation of the infinite beam, using sine wave road model of MW. Sayers vehicle road coupling system is used to calculate …and analyze the time history curve of traffic load. Then, plugged the loads into that the finite element, the initial dynamic stress and the counting of the influence of marine soft foundation depth was obtained under traffic loading. The results show that the vehicle road coupling system based on the balance mechanics method is effective. It can be extended to consider the stress of traffic loads and ocean soft foundation, and calculate the depth, considering the viscoelastic boundary. It effectively predicts the stress of marine soft soil foundation, and has important guiding significance for theoretical research and engineering practice. Show more

Keywords: Marine soft, traffic load, pavement coupling, finite element, viscoelastic boundary, intelligent

DOI: 10.3233/JIFS-179317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4811-4818, 2019

Authors: Liu, Lindong | Dai, Jingwen | Yang, Junwei | Jin, Miao | Jiang, Wei | Lu, Xingyu

Article Type: Research Article

Abstract: The occupational health and safety problems caused by indoor dust and toxic gases in industrial plants are becoming increasingly serious. Vertical push-pull ventilation can effectively control dust and toxic gases and avoid indoor environmental pollution. The velocity of the air supply hood and exhaust hood in the push-pull ventilation intelligent device directly affects the control effect of the dust and toxic gases. However, no scholar has given a reasonable ratio of the air supply and exhaust velocity of the vertical push-pull ventilation device. Therefore, this paper uses the combination of Fluent numerical simulation technology and smoke visualization experiment to explore …the best ratio of the air supply and exhaust velocity in the push-pull ventilation flow field. The research shows that the traces of the wind flow obtained by numerical analysis under different k which is the ratio of the air supply and exhaust velocity is consistent with the traces of visualized smoke in the actual experiment; The optimal ratio of air supply and exhaust is k  = 1.75, which can effectively guarantee the indoor environment, occupational health and work efficiency of the operators. Show more

Keywords: Dust and toxic gases, push-pull ventilation, ratio of the air supply, exhaust velocity, smoke visualization, intelligent

DOI: 10.3233/JIFS-179318

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4819-4826, 2019

Authors: Duan, Xiongying | Zhang, Fan | Liao, Minfu | Zou, Jiyan | Lv, Yang

Article Type: Research Article

Abstract: Controlled switching strategy can reduce overvoltages due to UHV transmission line closing. However, the traditional method is difficult to determine the quantitative relationship between the closing performance of circuit breakers and the risk of failure of transmission lines. Based on the risk of failure data calculated by the statistical method, an adaptive network-based fuzzy inference system (ANFIS) model for forecasting risk of failure that occurs during the closing of transmission lines is presented. An ANFIS model is employed to map the closing performance of circuit breakers and the risk of failure of the UHV transmission line. The model is based …on a system of fuzzy-rules written on the basis of previous results, the knowledge and experience. The fuzzication of input variables is carried out using fuzzy sets with the Gauss membership functions. “Grid partition” was used to generate the fuzzy inference system, and a hybrid learning rule was used to optimize the fuzzy system parameters. After the appropriate model is established through training and checking, it can forecast the risk of failure in different closing performance of circuit breakers. Then, it is easy to analyze the closing performance of circuit breakers in different risk of failure requirements. Show more

Keywords: ANFIS, closing performance, ultra-high-voltage, controlled switching, risk of failure

DOI: 10.3233/JIFS-179319

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4827-4836, 2019

Authors: Gan, Haiqing | Zheng, Chuiyong | Cui, Hantao

Article Type: Research Article

Abstract:  In this paper, in the so-called centralized charging and unified distribution mode, a two-stage optimization model is proposed for capacity planning and ordered discharging strategies of centralized charging stations considering the peak-shaving effects. Firstly, the operating states of battery pack are analyzed at each moment by combining with distribution modes, then the first stage planning is processed, that is, by taking the numbers of battery pack and generators as the control variables, the mathematical model aiming at minimizing the construction cost of centralized charging stations can be solved by Simulated Annealing Particle Swarm Optimization (SAPSO). Next, in the second stage …planning, in order to maximize the peaking effect of the centralized charging station, the cost function aiming at minimizing load variance is proposed, and the discharge power of each time can be obtained by using yalmip toolbox. Finally, simulation results are provided to verify the effectiveness and usefulness of the proposed optimization model. Show more

Keywords: Two-stage optimization model, centralized charging station, ordered discharge strategy, SAPSO algorithm

DOI: 10.3233/JIFS-179321

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4837-4846, 2019

Authors: Ji, Jiang-Tao | Yang, Lin-Hui | Jin, Xin | Ma, Hao | Pang, Jing | Huang, Rong-Biao | Du, Meng-Meng

Article Type: Research Article

Abstract: Pot seedling transplanting is the main way of vegetable planting, there were some problems of labor intensity and low level of automation in the process of mechanized transplanting of vegetable pot seedling. Aiming at this problem, this paper designed an intelligent transplanting system for vegetable pot seedling, which included the function of the seeding storage mechanism, the seedling feeding mechanism, the ejecting seedling mechanism, the pinch mechanism and the planting mechanism, the system monitors the whole movement process of planting through pressure sensing, stroke detection and limit switch, obtains each planting stage of the seedlings during planting, and uses the …CCD camera to identify the key steps of planting and seedlings to determine whether it is missing. Three broccoli seedlings with different moisture content and the age of 42d were used as the experimental object of seedlings planting experiment. Results indicated that: Under the conditions of meeting the agronomic requirements of vegetable pot seedlings, when the speed of picking-up seedlings was 75 seedlings per minute, which resulted in a 95% success rate of picking-up seedlings and 5% leaked seedlings rate, the planting effect of vegetable pot seedlings was the best. The research can provide useful reference for the development of intelligent transplanting technology of vegetable pot seedling. Show more

Keywords: Vegetable pot seedling, intelligent transplanting system, PLC control, design

DOI: 10.3233/JIFS-179322

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4847-4857, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4859-4859, 2019

Authors: Wang, Haofang | Yun, Ruan | Zhao, Ranhang | Qi, Zhen

Article Type: Research Article

Abstract: Flash flood is one of the most significant natural disasters in China, particularly in mountainous area, causing heavy economic damage and casualties of life. For numerous small hilly basins that need flash flood prevention and control with limited funds, it is necessary to give a priority order or to determine which basin needs to be harnessed firstly. Flash flood risk assessment is critical to an efficient flash flood management. Among many flash flood risk evaluation methods in literatures, variable fuzzy method (VFM) was chosen in this paper. To verify the results of VFM, fuzzy clustering analysis (FCA) is also used. …First, taking Licheng county with 119 small basins in China as an example, 9 indexes were identified among index system, based on disaster-breeding environment (or underlying surface conditions) of small basin in hilly region. Risk levels are divided into three grading levels such as high, medium and low. Second, VFM was introduced, and the flash flood risk grade eigenvalue (H) of each small basin was calculated. The results show that no small basin belongs to high risk level, 14 basins belong to low risk level, and the remaining 105 small basins belong to medium risk level. Third, FCA was used to verify the result of VFM. The results of two methods show that they are nearly in consistence. This paper shows that VFM is feasible for flash flood risk evaluation. Finally, the priorities for flash flood mitigation of 119 small watersheds in Licheng county are mapped out, which will provide effective help for flood disaster mitigation of small basin. Show more

Keywords: Variable fuzzy method, fuzzy clustering analysis, flash flood risk, disaster-breeding environment, small basin

DOI: 10.3233/JIFS-171089

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4861-4872, 2019

Authors: Khan, Asghar | Hadi, Asmat | Ibrar, Muhammad | Jun, Y.B.

Article Type: Research Article

Abstract: Using the notions of a soft set and a fuzzy set, Jun’s introduced a new type of notion called a hybrid structure, which is a generalization of soft set and fuzzy set. In this paper, we apply hybrid structure in hemirings and introduce the concept of hybrid h -ideals of hemirings and the related properties are investigated. Some operational properties of hybrid structures are first investigated. The concepts of a hybrid h -sum and a hybrid h -product are discussed and the related properties are investigated. The notions of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are …introduced and several properties are provided. The notion of a hybrid level set is introduced and the basic properties of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are studied in detail. The characterizations of h -hemiregular hemirings are discussed and several important results of a h -hemiregular hemirings are provided. Show more

Keywords: Hybrid structure, hybrid structures operations, hybrid h-sum, hybrid h-product, hybrid h-ideals, hybrid h-bi (h-quasi)-ideals, h-Hemiregular hemirings.

DOI: 10.3233/JIFS-171587

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4873-4889, 2019

Authors: Zhou, Yimin | Li, Zhifei

Article Type: Research Article

Abstract: This paper proposes a novel image processing method to extract the gender feature from frontal face combining Principal Component Analysis (PCA) and an improved Genetic Algorithm (GA) to reduce the interference of facial expression, lighting or wear. The collected facial images are first cropped and aligned automatically, then the gray-level information can be converted to feature vectors via PCA. After eigen-features are extracted with high classification performance by the aid of an improved GA, the neural network classifier can be trained accordingly. Compared to the classification methods based on global gray-level information, the obtained classifier has better identification rate but …less used feature dimension, so the calculation load can substantially be reduced during training and classification procedures, which benefits to the development of a real-time identification system. Furthermore, FERET dataset and FEI dataset are used to validate the generality of the proposed method, where 94% and 96% accuracy rates of the gender recognition can be achieved respectively. Show more

Keywords: Gender recognition, Genetic feature selection, Neural network, Principal component analysis, Frontal face

DOI: 10.3233/JIFS-17193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4891-4902, 2019

Authors: Samadi, Aliasghar | Jazaeri, Mostafa

Article Type: Research Article

Abstract:  An isolated network with Wind Turbine implemented by Double Fed Induction Generator (WTDFIG) that maintaining different electrical variables in safe ranges following a severe transient condition is always a serious challenge. This paper proposes a control scheme based on Auto-Tuning Fuzzy PI (ATFPI) concept for the Rotor Side Converter (RSC) of the DFIG by online tuning of the output scaling factor of the ATFPI for enhancement the transient behavior of the system under various condition of operation. The scheme includes a coordinator unit which is elaborated to effectively regulate the frequency and active power of the system. The performance of …the proposed ATFPI controller is evaluated in a typical network in Matlab Simulink environment. Obtained results show that the control can successfully meet all functions drawn in the scope and easily put behind the conventional competitors like conventional PI and/or fuzzy PI controllers. Show more

Keywords: DFIG, PI controller, fuzzy PI controller, modal analysis, transient condition, rotor side convertor

DOI: 10.3233/JIFS-171953

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4903-4921, 2019

Authors: Agarwal, Shikha | Dhyani, Akshay | Ranjan, Prabhat

Article Type: Research Article

Abstract: High dimensional data have brobdingnagian number of features, but not all features are useful. Irrelevant and redundant features may even reduce the classification accuracy. Feature selection is a process of selecting a subset of relevant features to decrease the dimensionality of data. When applied on high dimensional datasets (Big Data) the feature selection methods perceives many challenges and it is pertinent to come up with the new methods or revamp the existing methods. In this study, a new method ‘Newtonian particle swarm optimization (NPSO)’ has been proposed. In the proposed method Newton’s second law of motion has been used to …update the learning mechanism of PSO. In NPSO, particle not only learn from the position but also from the mass and acceleration of neighboring particles. The proposed method is mathematically validated at equilibrium using eigen values. Further, the proposed method has been applied on high dimensional microarray gene expression dataset. The NPSO is also compared with other state of art feature selection methods. Selected features, classification accuracy and dimension reduction are used to appraise the goodness of the proposed method. Mathematical validation and experimental results clearly validates the merits of the proposed method in field of feature selection. This paper show the classwise analysis of SRBCT, Brain1, 11-Tumor and 14-Tumor datasets. When number of classes increased dimension reduction is increased but classification accuracy of dataset is decreased. Show more

Keywords: Particle swarm optimization, law of motion, big data, microarray gene expression, cancer data, feature selection, classification accuracy

DOI: 10.3233/JIFS-181177

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4923-4935, 2019

Authors: Gałka, Jakub | Jaciów, Paweł

Article Type: Research Article

Abstract: In this paper, we propose a new method for concurrent accuracy and computational efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The design assumptions and an algorithm for a new type of fuzzy i-vector tree construction were introduced. The obtained solution was evaluated using the NIST 2014 i-Vector Speaker Recognition Machine Learning Challenge dataset. A 15% relative equal error rate reduction for a 74% reduction in computation time was achieved when compared to the baseline with only a 5.5% relative identification rate loss for discussed tree configurations.

Keywords: speaker recognition, fast identification, i-vector, fuzzy clustering, decision trees

DOI: 10.3233/JIFS-181359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4937-4949, 2019

Authors: Bernardes, Nemerson D. | Castro, Felipe A. | Cuadros, Marco A.S.L. | Salarolli, Pablo F. | Almeida, Gustavo M. | Munaro, Celso J.

Article Type: Research Article

Abstract: The use of the fractional PID controller or simply PIλ Dμ has brought the addition of two new parameters, λ and μ . Although this results in a greater flexibility, they make the tuning of the controller more complex and slower. One solution to this is the use of fuzzy logic to perform a self-tuning of the parameters. Through its rules of inference, the algorithm can determine a better tuning in real time. This article presents a practical application of a PIλ self-tuned with the use of fuzzy logic, in a differential mobile robot. …Three different types of speed controllers are presented. A lemniscate curve is used for the robot’s trajectory tracking, with and without disturbance in the speed control of the wheels. Dynamic selection of better controller parameters is obtained by the fuzzy controller and applied on the speed control of the wheels of a mobile robot. A camera is used as feedback for the tracking controller, so the real pose estimated is acquired through image processing. The self-tuning controllers are evaluated, compared to a fixed-tuning controller, with its parameters being acquired through traditional, well consolidated methods. The implementation, practical results and conclusions are hereby presented. Show more

Keywords: Backstepping control, fuzzy logic, PID controller, fractional control

DOI: 10.3233/JIFS-181431

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4951-4964, 2019

Authors: Solat, Alireza | Ranjbar, Ali Mohammad | Mozafari, Babak

Article Type: Research Article

Abstract: Doubly-fed induction generator (DFIG) is the most commonly used technology for wind power generation due to the variable speed performance, decoupled control of active and reactive powers, and high efficiency. However, the DFIG originally cannot participate in damping of power system oscillations since it is not synchronously connected to the power system. This paper proposes an optimal and robust additional damping controller for the DFIG wind turbine to contribute it to damp power system oscillations. It is a fuzzy logic controller that its parameters are optimally tuned using the genetic algorithm (GA). The proposed controller modifies the DFIG active power …output by using feedback from grid oscillations. Here, a comparative study is carried out for different feedback signals to determine the best of them. Comparing the results reveal that the rotor speed difference of synchronous generators is the best feedback signal to damp power system oscillations. Time domain simulations also confirm the effectiveness and robustness of the proposed controller under both the small and large disturbances. Show more

Keywords: Fuzzy logic, damping controller, doubly-fed induction generator, power system oscillations

DOI: 10.3233/JIFS-181524

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4965-4978, 2019