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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Wang, Jing | Wang, Ting
Article Type: Research Article
Abstract: Microgrids (MGs) are defined as a set of loads, generation sources and energy storage devices that act as a controllable load or generator, and can supply power and heat to local areas. Management of generated power in MGs is among the main topics that should be addressed for MG design and operation. The existence of distributed generation (DG) resources has caused MG management to face new issues. Depending on the level of exchange between the MG and main grid, MG operation can be classified into two modes: off-grid (islanded) and grid-connected. Optimal energy management in the systems with multiple MGs …has created new challenges in power systems. Therefore, it is important to develop energy management systems (EMSs) focusing on the optimal performance of MG resources and controlling power exchange between the grid and MGs. The present study aims to present a structure with two control layers, called primary and secondary control, for energy management in the systems with multiple MGs and different ownership. Moreover, a flexible distributed EMS is proposed to coordinate the operation of interconnected MGs. Each MG is regarded as an independent unit with local objectives to optimize its operating costs and exchanged power. It is assumed that interconnected MGs are connected to each other by a common bus, through which they can exchange power. MG planning is simulated considering load flow equations and voltage constraints in a system consisting of multiple MGs over a 24-h period. The simulation results indicate using the proposed EMS can improve MG efficiency and reliability. The simulation is performed in MATLAB software by grasshopper optimization algorithm (GOA). Uncertainties and scenario generation and reduction are considered in modeling. Show more
Keywords: Distributed energy management system, Microgrid (MG), distributed generation resource, power exchange
DOI: 10.3233/JIFS-220568
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7949-7961, 2022
Authors: Wang, Huifang | Zhang, Shili
Article Type: Research Article
Abstract: The compressive strength of high-performance concrete encounters difficulties in prediction due to supplementary cementitious materials in its mix designs. There are non-linear relationships between the input materials and the compressive strength. Distinguishing these relationships is intensified through innovative mix designs of high-performance concrete. Artificial neural networks based model incorporated in the present study to narrow down the intensified difficulties of compressive strength prediction. Moreover, to improve the robustness and flexibility of the model and reduce its complexity, Grey Wolf and Ant Colony Optimization algorithms optimize the ANN model. Different statistical metrics are employed to appraise the assessment of models. Considering …RMSE values, the values of ”GWANN-I ” and ”ACANN-I” are 1.6674 and 1.8653, respectively, delivering an acceptable performance in compressive strength prediction of HPC concrete. The OBJ values demonstrated that the ACANN-I with the value of 1.4499 outperforms best compared to other developed hybrid models and can be introduced as the best model for HPC compressive strength prediction. Show more
Keywords: Compressive strength, high-performance concrete, Grey Wolf Optimization, Ant Colony Optimization, artificial neural networks
DOI: 10.3233/JIFS-220736
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7963-7974, 2022
Authors: Yuvaraja, M.
Article Type: Research Article
Abstract: The use of wireless sensor networks (WSNs) for data collection is widespread. The resource constraint is an important factor in WSN communications design. The issue arises naturally in WSNs as a result of uneven energy consumption caused by multi-hop routing and dynamic network models, which substantially affects network lifetime. The nodes are dispersed over distant sensing areas and are powered by finite or limited energy batteries that are difficult to replace. The energy of nodes is reduced as a result of changes in network topology or the network’s lifespan and the main intention of this research is to figure out …how to make sensor networks last longer. The suggested study work focuses on a specific routing strategy for WSNs that employs the AO-star algorithm with a Fuzzy approach and link stability for extending the network lifetime. The technique chooses the optimum routing path by the sensing point to the receiving node based on how much energy is consumed, the smallest number of nodes with the shortest latency, and lower transmission loads with higher throughput. To compare the proposed strategy’s efficiency in energy consumption balancing and network lifespan enhancement, the proposed technique may achieve a 30% longer average network lifetime than the A-star algorithm. Show more
Keywords: Energy, fuzzy, loads, simulation data and WSN
DOI: 10.3233/JIFS-212977
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7975-7982, 2022
Authors: Wang, Liqin | Chu, Hang | Dong, Yongfeng | Liu, Enhai | Li, Linhao
Article Type: Research Article
Abstract: Many real-world knowledge graphs are complex and keep evolving over time. Inferring missing facts in temporal knowledge graphs is a fundamental and challenging task. Previous studies focus on link prediction in static knowledge graphs which hardly extracts the temporal features effectively. In this paper, we propose a novel deep learning model, namely KBGAT-BiLSTM, which is capable of solving long-term predict problems and is suitable for temporal knowledge graph with complex structures. First, we adapt the Graph Attention Network (GAT) to learn the structural features of knowledge graph. Then we utilize the Bidirectional Long Short-Term Memory Networks (BiLSTM) to learn the …temporal features and obtain the low-dimensional embeddings of entities and relations. Finally, we employ a scoring function for link prediction in temporal knowledge graphs. Through extensive experiments on YAGO, WIKI, and ICEWS18 datasets, we demonstrate the effectiveness of our model, compare the performance of our model with several different state-of-the-art methods and further analyze the properties of the proposed method. Show more
Keywords: Knowledge graph, link prediction, graph attention network, temporal
DOI: 10.3233/JIFS-210943
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7983-7994, 2022
Authors: Janardhan, G. | Surendra Babu, N. N. V. | Srinivas, G. N.
Article Type: Research Article
Abstract: A hybrid method for transformer-less grid-tie hybrid Renewable Energy Source (HRES), such as photovoltaic (PV) and wind energy system (WES) with minimization of common mode leakage current is proposed in this manuscript. The proposed system is the combined execution of Vascular Invasive Tumor Growth (VSTG) Optimization Algorithm and extreme gradient boosting (XGBOOST) named VSTG-XGBOOST control topology. The main intention of transformerless grid-connected HRES system is “to lessen the leakage current, maximum power point (MPP) extraction and maximal power point tracking (MPPT), the active and reactive power controller, and having the unity power factor. To attain the above-mentioned aims, the following …actions have been performed in this proposed work. Two turn-off snapper circuits are inserted parallel to the switches to share the input DC voltage among snubber capacitors. By then, VSTG is used to estimate the optimal gain parameters under various source currents as normal value is used to generate the optimal control signal database offline. Based on the attained dataset, the XGBOOST forecasts the optimal control signals of the grid-connected HRES inverter in the online way. This control technique allows two sources to supply the load separately depending on the availability of the energy sources and keeps common DC voltage constant. Show more
Keywords: Transformer-less grid-tie inverter, common mode leakage current, photovoltaic, Hybrid Renewable Energy Source, snubber capacitors
DOI: 10.3233/JIFS-213362
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7995-8019, 2022
Authors: Rashid, M.H.M. | Altaweel, Nifeen Hussain
Article Type: Research Article
Abstract: In this paper, we introduce a new fuzzy contraction mapping and prove that such mappings have fixed point in τ -complete fuzzy metric spaces. As an application, we shall utilize the results obtained to show the existence and uniqueness of random solution for the following random linear random operator equation. Moreover, we shall show the existence and uniqueness of the solutions for nonlinear Volterra integral equations on a kind of particular fuzzy metric space.
Keywords: Random fixed point, random operator, random operator equation, contractive mapping, fixed point, t-norm, fuzzy metric space, non-archimedean fuzzy metric space
DOI: 10.3233/JIFS-220258
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8021-8040, 2022
Authors: Thai, Pon L.T. | Merry Geisa, J.
Article Type: Research Article
Abstract: Cervical cancer is the most frequent and fatal malignancy among women worldwide. If this tumor is detected and treated early enough, the complications it causes can be minimized. Deep learning demonstrated significant promise when imposed on biomedical difficulties such as medical image processing and disease prognostication. Therefore, in this paper, an automatic cervical cell classification approach named IR-PapNet is developed based on Inception-ResNet which is an optimized version of Inception. The learning model’s conventional ReLu activation is replaced with the parametric-rectified linear unit (PReLu) to overcome the nullification of negative values and dying ReLu. Finally, the model loss function is …minimized with the SGD optimization model by modifying the attributes of the neural network. Furthermore, we present a simple but efficient noise removal technique called 2D-Discrete Wavelet Transform (2D-DWT) algorithm for enhancing image quality. Experimental results show that this model can achieve a top-1 average identification accuracy of 99.8% on the pap smear cervical Herlev datasets, which verifies its satisfactory performance. The restructured Inception-ResNet network model can obtain significant improvements over most of the state-of-the-art models in 2-class classification, and it achieves a high learning rate without experiencing dead nodes. Show more
Keywords: Cervical cancer, medical image processing, deep learning, 2D-DWT, ResNet model
DOI: 10.3233/JIFS-220511
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8041-8056, 2022
Authors: Chen, Zhihua | Kosari, Saeed | Kaarmukilan, S.P. | Yuvapriya, C. | Atanassov, Krassimir T. | Rangasamy, Parvathi | Rashmanlou, Hossein
Article Type: Research Article
Abstract: Video Processing has found enormous applications in recent times from security systems to interplanetary missions. In real-life situations, most of the videos are fuzzy/vague/uncertain. Intuitionistic fuzzy set (IFS) is one of the effective tools for handling uncertainty. Among many extensions of IFSs, temporal intuitionistic fuzzy sets (TIFSs) are very interesting as they are time-dependent. Hence, TIFSs are suitable to define a video, which is dynamic and hence depends on time-moment. In this way, this work introduces a novel VIdeo PROCessing (VIPROC) algorithm, using temporal intuitionistic fuzzy sets to enhance videos, which is first of its kind in existence. The comparison …is made with fuzzy contrast intensification operation. VIPROC algorithm is designed using contrast intensification operation for video enhancement. The results are encouraging in comparison with the original test videos. The results are discussed taking into account the several frames of the test video. Further, the proposed algorithm can be applied/extended to engineering applications like motion tracking, traffic detection systems, real time videos captured through mobile (hand-held) devices, and so on. As no such algorithms are existing which use TIFSs to process a video, the authors got motivated to design and develop VIPROC algorithm. Show more
Keywords: Temporal intuitionistic fuzzy sets, contrast intensification, VIdeoPROCessing (VIPROC) algorithm
DOI: 10.3233/JIFS-220928
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8057-8072, 2022
Authors: Annamalai, Tamizhselvi | Liju Anton, J. | Yoganathan, P.
Article Type: Research Article
Abstract: Intelligent transport system is a greatly emerging technology in recent years. The stability and reliability of these systems is very important. In vehicular ad-hoc networks (VANET), the data transmission process can be improved by employing clustering process. The nodes can be clustered in order to utilize the maximum bandwidth of the network and improving network stability. In VANETs it is to introduce road safety and driver safety. In addition, security is a major concern and the malicious nodes need to be accurately detected. Several kinds of attacks can present in the VANETs. Hence an efficient authentication method and trust aware …method is essentially required. In this work, stability assured CNN based trust aware clustering and authenticated transmission is introduced. For data authentication quantum cryptography technique is employed. In clustering process, trust degree of nodes is computed, vehicle speed is observed, direction of vehicle and distance among nodes are taken. In addition, for ensuring more safety, the critical data transmission is given higher priority. Therefore in clustering, data criticality parameter is also considered. For cluster formation, convolution neural network is employed. After the clustering process, the quantum cryptography based authentication is implemented for vehicle units and road side units. Data among these units are transmitted with quantum channel encryption key. Then simulation results are observed for validating the proposed protocol. Show more
Keywords: Vehicular ad-hoc networks, wireless communication, routing protocols, cryptography, convolution neural network
DOI: 10.3233/JIFS-220460
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8073-8087, 2022
Authors: Liu, Lu | Sun, Qiming | Jiang, Tianhua | Deng, Guanlong | Gong, Qingtao | Li, Yaping
Article Type: Research Article
Abstract: Recently, energy-saving scheduling issues have attracted more and more attention in the manufacturing field. Meanwhile, in practical production, maintenance planning is viewed as a vital task in the workshop. However, the existing literature about energy-saving scheduling problems rarely consider the effect of preventive maintenance. Therefore, this paper investigates an energy-saving flexible job shop scheduling problem with preventive maintenance. A mathematical model is proposed considering the minimization of total energy consumption. To solve the problem, a novel discrete elephant herding optimization algorithm (NDEHO) is proposed according to the problem’s characteristics. To test the NDEHO’s performance, the Taguchi design of experiment approach …is adopted to get the best combination of parameters in the algorithm. Numerical experiments are conducted based on twenty-four instances, including four benchmark instances and twenty randomly generated instances. Computational data indicate that NDEHO outperforms other compared algorithms for solving the considered problem. Show more
Keywords: Energy-saving scheduling, flexible job shop, preventive maintenance, total energy consumption, elephant herding optimization
DOI: 10.3233/JIFS-220494
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8089-8107, 2022
Authors: Cao, Wei Hang | Jiang, Jian
Article Type: Research Article
Abstract: In this paper, considering the heterogeneity of travelers’ decision-making behavior caused by travel environment factors, thus affecting the choice of travel path, the theories and methods of travel path choice based on improved cumulative prospect theory (ICPT) in complex environment were proposed. On the basis of cumulative prospect theory (CPT), the value function was improved, and the parameter value range was enlarged. The nonlinear curve of value function and weight function of cumulative prospect theory was fitted through thousands of data tests and experiments. Then according to the decision preference, the decision makers were divided into different categories and the …reference point value relationship of heterogeneous decision makers was found. In this paper, fuzzy travel time reference point and periodic dynamic risk degree reference point were set up, and a dynamic path selection model based on heterogeneous double reference point was established to improve the cumulative prospect value. Taking the highway network in Sichuan-Tibet region for example, the optimal path selection scheme of heterogeneous travel groups under the complex environmental factors such as debris flow and landslide in each time stage was studied, and the influence of preference parameter of travel time and risk degree on path choice was analyzed, and then the parameter sensitivity in the cumulative prospect theory (ICPT) was analyzed. The research results verified the rationality of the improved theory and method proposed in this study, which not only provide a new way of thinking for the study of travel path choice in complex environment but also provide theoretical guidance value for supporting regional traffic planning and construction in complex environment. Show more
Keywords: Path choice, complex environment, improved cumulative prospect theory, heterogeneous preference points, Sichuan-Tibet region
DOI: 10.3233/JIFS-220597
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8109-8126, 2022
Authors: Surya, R. | Mullai, M.
Article Type: Research Article
Abstract: Inventory managers are expected to handle a large number of items in their inventory while adhering to budgetary and space limits, as well as the number of items bought from vendors. Multi-item inventory models with one or more resource constraints, such as budget, space, or number of orders. This paper talks about an EOQ model in neutrosophic multi-item inventory control models with constraints. The ordering costs, the holding costs, demands, storage area, investment amount, and the maximum average number of units are considered as triangular neutrosophic numbers, as opposed to crisp values, to make the inventory model more realistic. This …idea is used to decide the neutrosophic optimal order quantities with the assistance of the Lagrange multiplier. Eventually, the proposed method is delineated with a numerical instance and the results are analysed briefly. Show more
Keywords: Inventory, space constraint, investment constraint, neutrosophic sets, triangular neutrosophic numbers
DOI: 10.3233/JIFS-221143
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8127-8136, 2022
Authors: Ni, Chenmin | Fam, Pei Shan | Marsani, Muhammad Fadhil
Article Type: Research Article
Abstract: GPS monitoring systems and the development of driverless vehicles are almost inseparable from camera images. The images taken by traffic cameras often contain certain sky areas and noise, the traditional dark channel prior (DCP) algorithm easily produces color distortion and halo effect, when processing the hazy traffic images with sky and high brightness areas. An optimized Retinex model and dark channel prior algorithm (ORDCP) is proposed in this paper. Firstly by adjusting the calculation method of dark channel image, the proportion of dark channel is improved; Then, the transmittance image is corrected and smoothed by guided filtering and mean filtering. …Finally, the Retinex model is fused to save the details.ORDCP corrects the inaccurate calculation of scene transmittance value in DCP algorithm,and modifies some dehazing problems, such as the loss of details, halo effect, contrast and color distortion,etc. Using information entropy (IE) as the objective evaluation index, combined with the subjective evaluation, it is concluded that the algorithm proposed in this paper can effectively retain the detailed information of the image, and eliminate the halo effect. Meanwhile, it meets the visual characteristics of human eyes better, and has some practicality and applicability in traffic control and intelligent detection. Show more
Keywords: Haze removal, traffic image, Retinex model, dark channel prior
DOI: 10.3233/JIFS-221240
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8137-8149, 2022
Authors: Jiang, Jian
Article Type: Research Article
Abstract: This research proposes a Pythagorean fuzzy multi-attribute decision-making evaluation method based on the improved cumulative prospect theory. The method ranks the decision-making results by calculating the comprehensive cumulative prospect value. Firstly, the research improves the cumulative prospect theory based on the utility curve, and describes the psychological and behavioral characteristics of various decision-making groups with different risk preferences. Then, a distance measure method based on the geometric center of the Pythagorean fuzzy right triangle is designed. The main core of the distance measure method is that it converts the Pythagorean fuzzy number into a Pythagorean fuzzy right triangle. In terms …of attribute weighting, this research proposes a subjective and objective weighting method based on the combination of value function and deviation method of improved cumulative prospect theory. Finally, the Pythagorean fuzzy multi-attribute decision-making method based on the improved cumulative prospect theory is realized through the selection of reference object, the calculation of value function value, weight function value and cumulative prospect value. The results analysis and the comparison with other methods verify the effectiveness and advancement of the proposed decision-making method, especially that the proposed method has good applicability for the decision-making cases where the attribute value is Pythagorean fuzzy number, the attribute weight is unknown, and the psychological behavior of decision makers cannot be reflected. Show more
Keywords: Ecological sustainable development, location selection of emergency rescue center, improved cumulative prospect theory, Pythagorean fuzzy number, subjective and objective weighting method, Sichuan-Tibet Railway
DOI: 10.3233/JIFS-221301
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8151-8175, 2022
Authors: Xu, Xinrui | Deng, Dexue
Article Type: Research Article
Abstract: The selection of suppliers is an important part of the construction of engineering projects in supply chain management. If the partners in the supply chain are reliable enough, they can promote the continuous progress of the supply and demand sides in the cooperation, thereby achieving a win-win situation, which is conducive to the realization of a virtuous cycle process. Material suppliers provide the required products and raw materials for the production and construction of enterprises. They are an important source of construction projects and occupy a very important position in the development of enterprises. The supply of high-quality products can …lay a good foundation for the subsequent production and construction of the project, thereby promoting the smooth completion of the entire project. Therefore, rational evaluation and selection of suppliers has very important practical significance. The selection and application of building material suppliers is a classic multiple attribute decision making (MADM). In this paper, we introduced some calculating laws on intuitionistic fuzzy sets (IFSs), Hamacher sum and Hamacher product and further propose the induced intuitionistic fuzzy Hamacher power ordered weighted geometric (I-IFHPOWG) operator. Meanwhile, we also study some ideal properties of built operator. Then, we apply the I-IFHPOWG operator to deal with the multiple attribute decision making (MADM) problems under IFSs. Finally, an example for physical health literacy evaluation of College students is used to test this new approach. Show more
Keywords: Multiple attribute decision making (MADM), intuitionistic fuzzy sets (IFSs), I-OWG operator, I-IFHPOWG operator, building material suppliers
DOI: 10.3233/JIFS-221869
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8177-8186, 2022
Authors: Shi, Haosu | Han, Lina | Fang, Linbo | Dong, Huan
Article Type: Research Article
Abstract: An improved algorithm of image defogging was proposed based on dark channel prior in order to solve the low efficiency and color distortion in the bright area using original algorithm. If the image contains large areas of bright areas such as sky, white clouds or partial white objects and water surface, we can know that the dark channel prior theory does not apply to these areas. Firstly, it is necessary to clear the bright area of the image. According to principle that he adjacent pixel attributes have similarity, the image transmittance of the local region also has similarity, Block function …is Consruted. Applied the dark channel prior, judging whether each block includes a bright area by the absolute value of difference of atmospheric intensity and dark channel, the dark and bright areas of the image are obtained. So the estimation value of the adaptive space transmittance are also obtained. Secondly, the transmittance of bright region is small and it causes deviation, so the enhancement formula is used to modify it dynamically. In order to preserve the edge details after image restoration, for bright areas, using texture function to optimize transmittance independently, for others, using gradient and texture function together. Finally, it restored the fog-free image applying the atmospheric scattering model. The experimental results showed that the restored image had obvious details and rich color and fast processing speed through the proposed algorithm. The algorithm can also be applied to outdoor visual systems, such as video surveillance, intelligent traffic and so on. Show more
Keywords: Dark channel prior (DCP), image defogging, gradient information, texture information, transmittance, atmospheric scattering model
DOI: 10.3233/JIFS-221521
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8187-8193, 2022
Authors: Zhang, Lei | Bai, Wei | Guo, Shize | Xu, Youwei | Jiang, Kaolin | Pan, Yu | Zheng, Qibin | Chen, Jun | Pan, Zhisong
Article Type: Research Article
Abstract: Because multiple domain cyberspace joint attacks are becoming more widespread, establishing a multiple domain cyberspace defensive paradigm is becoming more vital. However, although some physical domain and social domain information is incorporated in present approaches, total modeling of cyberspace is absent, therefore thorough modeling of cyberspace is becoming increasingly necessary. This paper proposed a knowledge graph based multiple domain cyberspace modeling approach. A knowledge graph of multiple domain cyberspace is produced by extracting multiple domain entity information and entity relations such as physical domain, social domain, network domain, and information domain, so that semantic information of multiple domain cyberspace may …be described consistently. At the same time, this paper proposed a user’s permissions reasoning method based on multiple domain cyberspace knowledge graph to address the user’s permissions reasoning that relies on artificial reasoning principles. Through the model learning knowledge graph triples characteristics and rules, and implementing automatic reasoning of user’s permissions, this proposed method can abandon the artificial model of writing reasoning rules, allowing the machine to learn the reasoning rules using machine learning and other methods. Experimental results showed that the proposed method can learn relevant reasoning rules and accomplish automated reasoning of user’s permissions, and that the method’s accuracy and recall rates are higher than those of path ranking and translating embeddings. Show more
Keywords: Multi-domain cyberspace, knowledge graph, unified semantic description, user’s permissions reasoning, intelligent
DOI: 10.3233/JIFS-211696
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8195-8206, 2022
Authors: Rikhtechi, Leila | Rafeh, Vahid | Rezakhani, Afshin
Article Type: Research Article
Abstract: One of the most significant issues in information security today is monitoring users’ behavior while accessing software resources. This paper proposes a new access control model based principally on user behavior as a sequence of events regarding the processes within the software. The proposed model consists of three main components. The first component analyses system logs for events triggered by each user’s access to the system. The second component provides a policy engine to determine the risk of permitting the subsequent access requested by the user. According to the access history, the third component, which reflects the user’s behavior and …the existing policies, determines the level of risk of any subsequent access of the user and acts accordingly. To generate the policies in the detection engine, a behavior-based risk management cycle is presented by applying the Ordered Weighted Averaging method to determine and rank the behavior-based risks. For modeling the behaviors, the BIZAGI Studio tool is utilized, and also for investigating all possible conditions. Kaggle and two random datasets are used to evaluate the accuracy of the proposed method. The results show an increase in the accuracy of the proposed method compared to recent research. Applying the proposed method creates more precise access control and enhances information confidentiality. Show more
Keywords: Users’ behavior, access control, ordered weighted averaging, behavior-based risk management, software
DOI: 10.3233/JIFS-212377
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8207-8220, 2022
Authors: Anand, R.
Article Type: Research Article
Abstract: This paper is to improve the privacy and security in the distributed virtual environment using blockchain technology. One of the feature it provides is greater security in the decentralized virtual environment. A key aspect of this technology is used for various fields like healthcare, finance, business and cloud environment. Key issue of the virtual environment is to protect the data privacy and security which is difficult to handle. To overcome this issue, a new security model to protect the virtual environment is created and will focus on different types of attacks in blockchain technology.
Keywords: Blockchain security, virtualization, virtual security, privacy
DOI: 10.3233/JIFS-212619
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8221-8231, 2022
Authors: Erdebilli, Babek | Aslan Özşahin, Selcen Gülsüm
Article Type: Research Article
Abstract: Facility location models have been studied in the literature for decades as an outstanding branch of supply chain planning. Set-covering facility location models are among the most commonly used approaches to establishing and running a distribution network. However, real-life brings uncertain and imprecise parameters that need to be reflected in the model systematically and computably to achieve more efficient and precise solutions. That’s why fuzzy set covering models have been introduced in the literature from various perspectives. This work aimed to handle real-life uncertainties in an unbiased and autonomous way and provide more precise solutions to fuzzy set-covering facility location …models in real-life contexts. Therefore, we propose a novel approach, adopting the autonomous fuzzy methodology consisting of fuzzy trapezoidal set coverage to minimize the cost of establishing new facilities. This work’s main innovative achievements are that i) the set-covering facility location models were equipped with autonomous uncertainty management ability, ii) the trapezoidal fuzzy set coverage constituted a perfect fit for the management of uncertainties in a realistic way in the model, and iii) the relevant fuzzification was executed without any human/expert intervention/supervision. The well-known Turkish Network Data demonstrated the proposed model’s efficacy. Furthermore, the results show that the developed model contributed to the overall theoretical framework of fuzzy approach employment in optimization models and outperformed classical version in numerical experiments. Show more
Keywords: Autonomous fuzzy optimization, data-driven set covering, autonomous fuzzy set covering, trapezoidal fuzzy set covering, trapezoidal fuzzy coverage
DOI: 10.3233/JIFS-213220
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8233-8246, 2022
Authors: Anu Shalini, T. | Sri Revathi, B.
Article Type: Research Article
Abstract: This paper presents the design of a grid connected hybrid system using modified Z source converter, bidirectional converter and battery storage system. The input sources for the proposed system are fed from solar and wind power systems. A modified high gain switched Z source converter is designed for supplying constant DC power to the DC-link of the inverter. A hybrid deep learning (HDL) algorithm (CNN-BiLSTM) is proposed for predicting the output power from the hybrid systems. The HDL method and the PI controller generates pulses to the proposed system. The superiority of the proposed hybrid DL method is compared with …the conventional DL methods like CNN, LSTM, BiLSTM methods and the performance of the hybrid system is validated. A closed loop control framework is implemented for the proposed grid integrated hybrid system and its performance is observed by implementing the PI, Fuzzy and ANN controllers. A 1.5Kw hybrid system is designed in MATLAB/SIMULINK software and the results are validated. A prototype of the proposed system is developed in the laboratory and experimental results are obtained from it. From the simulation and experimental results, it is observed that the ANN controller with SVPWM (Space vector Pulse width Modulation) gives a THD (Total harmonic distortion) of 2.2% which is within the IEEE 519 standard. Therefore, from the results it is identified that the ANN-SVPWM method injects less harmonic currents into the grid than the other two controllers. Show more
Keywords: Power forecasting, timeseries forecasting, bidirectional long short-term memory, convolution neural network, renewable power generation
DOI: 10.3233/JIFS-220307
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8247-8262, 2022
Authors: Radhakrishnan, C. | Asokan, R.
Article Type: Research Article
Abstract: To safeguard private information, image steganography is extensively used. Research is focused on ways to enhance steganographic technologies so that they may increase compression ratio while maintaining steganography image integrity. Because of its essential qualities such as security, scalability, and robustness, Steganography is a preferred way of communicating protected secret information to prevent hacking and misuse. This proposed research offers a steganography approach based on Enhanced Chaotic Particle Swarm Optimization (ECPSO), which uses chaos theory to determine the optimal pixel positions in the cover picture to hide confidential information when keeping the steganography quality in the images. Both the cover …and secret pictures are separated into blocks to increase hiding capacity, with each component storing a sufficient quantity of secret data by mapping the pixels. The suggested ECPSO-Stegano system has better results with the criteria of Mean Square Error (MSE) of 0.00018%, Peak-Signal-to-Noise-Ratio (PSNR) of 79.66%, Bit Error Rate (BER) of 0.45% in average, and Structural Similarity Index (SSI) of 0.98 in average for various input size. It’s also robust to statistical threats. Show more
Keywords: Chaos map, BET, Stego-image, blocks, optimal pixel, confidentiality
DOI: 10.3233/JIFS-221093
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8263-8273, 2022
Authors: Sammeta, Naresh | Parthiban, Latha
Article Type: Research Article
Abstract: In recent times, a number of Internet of Things (IoT) related healthcare applications have been deployed for automating healthcare services and offering easy accessibility to patients. Several issues like security, fault-tolerant, and reliability have restricted the utilization of IoT services in real-time healthcare environments. To achieve security, blockchain technology can be utilized which offers effective interoperability of healthcare databases, ease of medical data access, device tracking, prescription database, hospital assets, etc. Therefore, this paper presents an optimal Elliptic curve cryptography-based encryption algorithm for a blockchain-enabled medical image transmission model, named OECC-BMIT. The presented OECC-BMIT model involves different stages of operations …such as encryption, optimal key generation, blockchain-enabled data transmission, and decryption. Firstly, the OECC-BMIT model performs Elliptic curve cryptography (ECC) based encryption technique to securely transmit the medical images. In order to generate the optimal set of keys for the ECC technique, modified bat optimization (MBO) algorithm is applied. Then, the encrypted images undergo secure transmission via blockchain technology. The encrypted images are decrypted on the recipient side and the original medical image is reconstructed effectively. Extensive sets of experimentations were performed to highlight the goodness of the OECC-BMIT algorithm and the obtained results pointed out the improved outcome over the state of art methods in terms of different measures. Show more
Keywords: Blockchain, encryption, healthcare, medical images, optimal key generation
DOI: 10.3233/JIFS-211216
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8275-8287, 2022
Authors: Ren, Yaxue | Wen, Yintang | Liu, Fucai | Zhang, Yuyan
Article Type: Research Article
Abstract: Chaotic systems are dynamic systems with aperiodic and pseudo-random properties, and systems in many fields exhibit chaotic time-series properties. Aiming at the fuzzy modeling problem of chaotic time series, this paper proposes a new fuzzy identification method considering the selection of important input variables. The purpose is to achieve higher model modeling and prediction accuracy by constructing a model with a simple structure. The relevant input variable was swiftly chosen in accordance with the input variable index after the Two Stage Fuzzy Curves method was used to determine the weight of the correlation between each input variable and the output …from a large number of selectable input variables. The center and width of the irregular Gaussian membership function were then optimized using the fuzzy C-means clustering algorithm and the particle swarm optimization technique, which led to the determination of the fuzzy model’s underlying premise parameters. Finally, the fuzzy model’s conclusion parameters were determined using the recursive least squares method. This model is used to simulate three chaotic time series, and the outcomes of the simulation are contrasted and examined. The outcomes demonstrate that the fuzzy identification system has higher prediction accuracy based on a simpler structure, demonstrating its validity. Show more
Keywords: Fuzzy identification, input variable selection, chaotic time series, fuzzy c-means algorithm, irregular gaussian function
DOI: 10.3233/JIFS-212527
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8289-8301, 2022
Authors: Alshareef, Esam Alsadiq | Ebrahim, Fawzi Omar | Lamami, Yosra | Milad, Mohamed Burid | Eswani, Mohamed S.A. | Bashir, Sedigh Abdalla | Bshina, Salah A.M. | Jakdoum, Anas | Abourqeeqah, Asharaf | Elbasir, Mohamed O | Elbahrit, Ellafi.A.
Article Type: Research Article
Abstract: Knee osteoarthritis severity grading from plain radiographs is of great significance in the diagnosis of osteoarthritis (OA). Recently, deep learning had a great impact on improving the Kellgren and Lawrence (KL) grading scheme of Knee osteoarthritis KOA using models that acquire the contextual features spontaneously without the need for any conventional high computational spatial configuration modeling. In this study, we apply the state-of-art Vision Transformer (ViT) for the KL grading of Knee Osteoarthritis and show that a simple transfer learning approach of such model can lead to better results than those achieved by other complex architectures over less number of …training data. The study concludes that such a pre-trained ViT, fine-tuned on OAI dataset yield to promising results in KL grading KOA, in which these results are in line with the state-of-art studies. Show more
Keywords: Knee, severity, radiographs, grading, models, feature
DOI: 10.3233/JIFS-220516
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8303-8313, 2022
Authors: Harikumar, Sandhya | Sathyajit, Rohit | Karumudi, Gnana Venkata Naga Sai Kalyan
Article Type: Research Article
Abstract: News feeds generate colossal amount of data consisting of important information hidden in the intricacies. State of the art methods are still at infancy in providing a very generic and publicly available solution to skim through the important information in the news from various sources and an ability to search using specific keywords in different languages. This paper focuses on designing a tool to extract semantic details from news articles published through various internet sources in various languages. The semantic information is stored within DBMS for ease of organizing and retrieving the data. Further, a querying facility to search through …entire articles based on the keyword or date-based search is also proposed to view the crisp content. The news articles in English, and two Indian languages - Hindi and Malayalam are considered for experimentation. The proposed strategy consists of two main components namely, Generative model creation and Query engine. Generative model aims to extract important entities and keywords along with their relevance to the article and other similar articles using Latent Dirichlet Allocation(LDA) and Named Entity Recognition(NER). Query engine is to facilitate on the fly retrieval of semantic content from the database, based on user keyword. The search engine, along with database indexing, reduces the access time to the database thereby retrieving the information in less time. Experimental results show that the proposed method is effective in terms of quality of information and time consumed for information retrieval. Show more
Keywords: News analytics, multilingual, natural language processing(NLP), Latent dirichlet allocation(LDA), semantic information retrieval
DOI: 10.3233/JIFS-221184
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8315-8327, 2022
Authors: Senthamizh Selvi, S. | Anitha, R.
Article Type: Research Article
Abstract: In India, most of the Science and Technology resources available are in English. Developing an Automatic Language Translation Engine from English (source language) to Tamil (target language) is very essential for the people who need to get technical resources in their native language. The challenges in designing such engines using Natural Language Processing (NLP) tools include Lexical, Structural, and Syntax level ambiguity. To solve these challenges, the development of a Part-Of-Speech (POS) tagger is essential. The Verb-Framed languages like Tamil, Japanese, and many languages in Romance, Semitic, and Mayan languages families have high morphological richness but lack either a large …volume of annotated corpora or manually constructed linguistic resources for building POS tagger. Moreover, the Tamil Language has a low resource, high word sense ambiguity, and word-free order form giving rise to challenges in designing Tamil POS taggers. In this paper, we postulate a Hybrid POS tagger algorithm for Tamil Language using Cross-Lingual Transformation Learning Techniques. It is a novel Mining-based algorithm (MT), which finds equivalent words of Tamil in English on less volume of English-Tamil bilingual unannotated parallel corpus. To enhance the performance of MT, we developed Tamil language-specific auxiliary algorithms such as Keyword-based tagging algorithm (KT) and Verb pattern-based tagging algorithm (VT). We also developed a Unique pair occurrence-tagging algorithm (UT) to find the one-time occurrence of Tamil-English pair words. Our experiments show that by improving Context-based Bilingual Corpus to Bilingual parallel corpus and after leaving one-time occurrence words, the proposed Hybrid POS tagger can predict 81.15% words, with 73.51% accuracy and 90.50% precision. Evaluations prove our algorithms can generate language resources, which can improve the performance of NLP tasks in Tamil. Show more
Keywords: Natural language processing, part-of-speech tagger, sandhi, bilingual parallel corpus, cross-lingual transformation learning
DOI: 10.3233/JIFS-221278
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8329-8348, 2022
Authors: Rajesh, D. | Kiruba, D. Giji
Article Type: Research Article
Abstract: A basic need in smart dust network is to accomplish energy proficiency during routing as sensor nodes have rare energy asset. Node’s mobility in smart dust represents a challenge to intend energy proficient routing algorithm. Clustering accomplishes energy effectiveness by diminishing association complication aloft of network is comparative to quantity of moveable smart dust nodes in network. This research methodology proposes novel Energy Efficient Secured CH Clustered Routing (E2 SCR) in Smart Dust tactic. A smart dust node is chosen as cluster head in event that it has high superfluous energy, better communication range and low mobility. Energy responsive (ER) …selection method and Maximal Nodal Superfluous Energy assessment method combined with this method to enhance energy conception during routing. Simulation results demonstrate that proposed clustering and routing algorithm is unique and energy efficient smart dust network. Show more
Keywords: Smart dust, clustering, cluster-head, superfluous energy, energy responsive
DOI: 10.3233/JIFS-212012
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8349-8357, 2022
Authors: Gopinath, N. | Prayla Shyry, S.
Article Type: Research Article
Abstract: As technology advances, it becomes easier to share large amounts of data over the internet. Cloud computing is one of the technologies that allows for easy data sharing over the internet. It is critical to provide security for this data when they are being shared across the internet. The security of data saved in cloud storage, as well as data transport and transmitting a key required to encrypt data between two parties, has been a source of concern for the industry, as a result of the growing use of cloud services in recent years. Collective attacks are significantly more powerful …than individual strikes, according to our research. Despite the fact that additional research works were studied in the previous literature review, there are some study concerns for not correcting third-party data hacking. Therefore, this paper focuses on the design of Secured Quantum Key Distribution (SQKD) with Fuzzy logic to improve the security of the shared key. Quantum Key Distribution, Post Quantum Key Distribution, and the EPR Proto-col are technologies that increase the security of data sharing. We have incorporated the Secured Quantum Key Distribution (SQKD) with Fuzzy logic in our proposed work to improve the security of the shared key. The proposed systems include some additional characteristics in addition to the existing approaches. The proposed model uses shifting algorithms and the fuzzification procedure to assure the security of the secret key in the Fuzzification of Quantum Key approach. The experimental results states that the mean value of security losses in SFQ is 1.8306051, and the mean value of QKD is 14.6448416, with standard deviations of 1.7329 and 13.863 for SFQ and QKD, respectively. Show more
Keywords: Quantum key distribution, fuzzy logic, SQKD, Q-bits and quantum cryptography
DOI: 10.3233/JIFS-220398
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8359-8369, 2022
Authors: Wei-Jie, Lucas Chong | Chong, Siew-Chin | Ong, Thian-Song
Article Type: Research Article
Abstract: Masked face recognition embarks the interest among the researchers to find a better algorithm to improve the performance of face recognition applications, especially in the Covid-19 pandemic lately. This paper introduces a proposed masked face recognition method known as Principal Random Forest Convolutional Neural Network (PRFCNN). This method utilizes the strengths of Principal Component Analysis (PCA) with the combination of Random Forest algorithm in Convolution Neural Network to pre-train the masked face features. PRFCNN is designed to assist in extracting more salient features and prevent overfitting problems. Experiments are conducted on two benchmarked datasets, RMFD (Real-World Masked Face Dataset) and …LFW Simulated Masked Face Dataset using various parameter settings. The experimental result with a minimum recognition rate of 90% accuracy promises the effectiveness of the proposed PRFCNN over the other state-of-the-art methods. Show more
Keywords: Covid-19, PRFCNN, random forest, principal component analysis, convolutional neural network
DOI: 10.3233/JIFS-220667
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8371-8383, 2022
Authors: Levitan, Boris A. | Dinyaeva, Nellie S. | Sudarenko, Dmitry A. | Lyutov, Alexey V.
Article Type: Research Article
Abstract: The article discusses the production of microwave components based on the technology of low-temperature co-fired ceramics (LTCC). A set of standards Continuous Acquisition and Life cycle Support (CALS) and International Organization for Standardization (ISO) and business process models in these standards are considered. Based on the basic models of the ISO and CALS standards, a structural-parametric description model (SPD) has been developed, in which the structure of ISO-9000 is preserved, and specific parameters of LTCC technology are added. The methodology of the (SPD) of this technology is proposed. Open source software for processes, resources, results, production operations, control and management …has been developed for each technological operation (TO), workplace and area. The methodology for creating information support and Microsoft Access Database Management System (DBMS) of SPD is proposed. Recommendations for the development of a software-methodological complex of information support for SPD of LTCC technology are proposed. Show more
Keywords: Low-temperature co-fired ceramics, ISO-9000, CALS, method of structural parametric description, information support, structural-parametric description model of low-temperature co-fired ceramics, Microsoft Access Database Management System
DOI: 10.3233/JIFS-220889
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8385-8395, 2022
Authors: Periasamy, Madhumathi | Kaliannan, Thenmalar
Article Type: Research Article
Abstract: Microgrids (MGs) are distributed generation and distribution systems that include distributed generation (DG) units, energy storage systems (ESSs), distributed reactive sources (DRSs), and resilient loads that can operate in either connected or isolated modes. When dealing with uncontrolled DGs such as Wind Energy Systems (WES) and Photovoltaic Energy Systems (PVES), MGs planners have a difficult time making decisions. The work proposed in this paper addresses three interconnected works: (i) the implementation of a rigorous hybrid optimization approach for reconfiguration and DGs placement; (ii) the performance investigation under uncertain behavior of RES-based DGs and demand; and (iii) performance enhancement realization through …the replacement of hybrid DGs for RES-based DGs. An Improved Moth Flame Optimization (IMFO), which is a multi-objective optimization method, has been linked with fuzzy logic in order to handle multiple objectives in an efficient manner. These objectives include the minimization of voltage deviation, the reduction of generation cost, and the reduction of loss. The quality of the power, the amount of money saved by consumers, and the benefits to the Distribution System Operator (DSO) might all be improved with the help of a hybrid algorithm. This research is also extended to address the uncertainties of RES-based DGs by replacing hybrid DGs in the most optimal locations. IEEE 33 bus RDS is used to test radial distribution system (RDS) microgrids. For validation purposes, uses 24-hour load patterns to mimic WES and PVES’ 24-hour load dispatching behavior. The research findings clearly demonstrate the advantages of microgrids over traditional architectures. The hybrid DG requires an average generating cost of 185.33 $/kW in order to produce 100 kW of power throughout the day with significantly reduced emissions. Show more
Keywords: Renewable energy sources, radial distribution system, optimization, whale optimization algorithm, power loss
DOI: 10.3233/JIFS-221363
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8397-8415, 2022
Authors: Rauthan, J.S.
Article Type: Research Article
Abstract: Fully Homomorphic Encryption (FHE) is the holy grail of encrypted communications. It opens the door to several advanced functionalities to overcome the security and trust issues of the IT world. After 2009, once Craig Gentry had shown that FHE could be achieved, a study in this field boomed, and significant improvement was made in identifying more efficient and realistic programs. FHE is primitive cryptography that enables arbitrary functions to be calculated via encrypted data. These systems are applicable in different ways since they permit users to encrypt their private information securely while still outsourcing the processing of protected data without …fearing disclosing the real data. In 2012, LTV12 presented the first multi-key FHE system and demonstrated the possibility of using multi-key systems in somewhat homomorphic encryption (SHE). Like in the one key context, there have been many advances in the field, but no effort has been made to develop the multi-key methods. This paper presents a discussion of FHE and MKFHE with a specific focus on the current techniques and three implementations, comprising the first in the multi-key setups, to the extent of our understanding. Show more
Keywords: Fully Homomorphic Encryption (FHE), Multi-Key FHE(MKFHE), public-key cryptography, Learning With Errors (LWE), GSW
DOI: 10.3233/JIFS-221454
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8417-8437, 2022
Article Type: Retraction
DOI: 10.3233/JIFS-219323
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8439-8439, 2022
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