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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: Qazi, Emad-ul-Haq | Hussain, Muhammad | Aboalsamh, Hatim
Article Type: Research Article
Abstract: Representation and classification of Electroencephalography (EEG) brain signals are critical processes for their analysis in cognitive tasks. Particularly, extraction of discriminative features from raw EEG signals, without any pre-processing, is a challenging task. Motivated by nuclear norm, we observed that there is a significant difference between the variances of EEG signals captured from the same brain region when a subject performs different tasks. This observation lead us to use singular value decomposition for computing dominant variances of EEG signals captured from a certain brain region while performing a certain task and use them as features (nuclear features). A simple and …efficient class means based minimum distance classifier (CMMDC) is enough to predict brain states. This approach results in the feature space of significantly small dimension and gives equally good classification results on clean as well as raw data. We validated the effectiveness and robustness of the technique using four datasets of different tasks: fluid intelligence clean data (FICD), fluid intelligence raw data (FIRD), memory recall task (MRT), and eyes open / eyes closed task (EOEC). For each task, we analyzed EEG signals over six (06) different brain regions with 8, 16, 20, 18, 18 and 100 electrodes. The nuclear features from frontal brain region gave the 100% prediction accuracy. The discriminant analysis of the nuclear features has been conducted using intra-class and inter-class variations. Comparisons with the state-of-the-art techniques showed the superiority of the proposed system. Show more
Keywords: Electroencephalography (EEG), nuclear features, singular value decomposition (SVD), fluid intelligence, class means based minimum distance classifier (CMMDC)
DOI: 10.3233/JIFS-181586
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 913-928, 2019
Authors: Khalil, Ahmed Mostafa | Li, Sheng-Gang | Li, Hong-Xia | Ma, Sheng-Quan
Article Type: Research Article
Abstract: The major concern of this paper is to highlight the notion of possibility m -polar fuzzy soft set (because it is useful in decision-making and other similar problems). For convenience of practical applications, several operations (such as subset, equal, complement, union, intersection, inf product, and sup product) over the possibility m -polar fuzzy soft sets are introduced. We present two algorithms by using inf product or sup product operations of possibility m -polar fuzzy soft sets for fuzzy decision-making problem. Finally, we construct an algorithm using a possibility m -polar fuzzy soft set to solve the decision-making problems and illustrate …its applicability through a numerical example. From the study, we conclude that the proposed approach is viable in order to handle the uncertainties during the decision-making problems. Show more
Keywords: m-polar fuzzy set, m-polar fuzzy soft set, possibility m-polar fuzzy soft set, decision-making
DOI: 10.3233/JIFS-181769
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 929-940, 2019
Authors: Kececioglu, O. Fatih
Article Type: Research Article
Abstract: Maximum Power Point Tracking (MPPT) is one of the major functions of PV system because of the performance of PV system directly affected by atmospheric conditions. This paper first presents a novel configuration for MPPT of PV system. This configuration is combined with modified positive luo converter that is high gain dc-dc converter and Type-2 fuzzy neural network controller (T2FNNC). Modified positive luo converter that has high voltage gain and conversion efficiency is suitable for the two-stage grid integrated solar photovoltaic system. The main advantage of proposed configuration is high performance and stability against to disturbance inputs such as solar …radiation and panel temperature variations. To validate the performance of this configuration, a simulation model is built by using Matlab/Simulink. The simulation results show that proposed configuration based on modified positive output luo converter with T2FNN has a superior performance than conventional PI controllers in terms of MPP tracking efficiency under changing atmospheric conditions. Show more
Keywords: Robust control, Type-2 FNN, MPPT, modified positive output Luo converter
DOI: 10.3233/JIFS-181770
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 941-951, 2019
Authors: Abd El-latif, A.A.
Article Type: Research Article
Abstract: This paper is devoted to introduce and study new kinds of FP -multifunctions, namely FP -lower (upper) α -continuous, FP -lower (upper) almost α -continuous, and FP -lower (upper) weakly α -continuous multifunctions. Various properties of these multifunctions were investigated. We provided the relationships between these multifunctions and presented contrary examples. Finally, we gave the conditions which make these multifunctions equivalent.
Keywords: L-Fuzzy bitopological spaces, FP-lower (upper) α-continuous multifunctions, FP-lower (upper) almost α-continuous multifunctions, FP-lower (upper) weakly α-continuous multifunctions
DOI: 10.3233/JIFS-181791
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 953-964, 2019
Authors: Ding, Quanyu | Wang, Ying-Ming
Article Type: Research Article
Abstract: This paper investigates a method to deal with multiple attribute group decision making (MAGDM) problems in which the decision makers’ weights are expressed as crisp numbers, the weights of attributes are unknown, and attribute values are expressed as interval-valued trapezoidal intuitionistic fuzzy numbers (IVTrIFNs). Firstly, some new aggregation operators are proposed, including the interval-valued trapezoidal intuitionistic fuzzy weighted geometric averaging (IVTrIFWGA) operator, the interval-valued trapezoidal intuitionistic fuzzy ordered weighted geometric averaging(IVTrIFOWGA) operator, and the interval-valued trapezoidal intuitionistic fuzzy hybrid geometric averaging (IVTrIFHGA) operator. Some desirable properties of these operators are studied. The results of using these operators for aggregation are …also interval-valued trapezoidal intuitionistic fuzzy numbers. Secondly, a fuzzy cross-entropy of interval-valued trapezoidal intuitionistic fuzzy sets(IVTrIFSs) is defined, based on which a new mathematical model is established to determine the weights of attributes. Finally, the fuzzy grey relation analysis (GRA) is utilized to rank decision alternatives. Numerical examples are provided to demonstrate the effectiveness of the proposed multiple attribute group decision making method and its advantages in overcoming the defects of the existing methods. Show more
Keywords: Multiple attribute group decision making, IVTrIFWGA operator, IVTrIFOWGA operator, IVTrIFHGA operator, fuzzy cross-entropy, grey relation analysis
DOI: 10.3233/JIFS-181810
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 965-980, 2019
Authors: Donghai, Liu | Yuanyuan, Liu | Xiaohong, Chen
Article Type: Research Article
Abstract: Considering that the existing cosine similarity measure between hesitant fuzzy linguistic term sets(HFLTSs) has an impediment as it does not satisfy the axiom of similarity measure, we propose a new similarity measure of HFLTSs in the paper, which is constructed based on the existing cosine similarity measure and Euclidean distance measure of HFLTSs. Then the corresponding distance measure of HFLTSs is obtained according to the relationship between the similarity measure and the distance measure. Furthermore, we develop the TOPSIS method to the proposed distance measure in hesitant fuzzy linguistic decision environment and apply the closeness coefficients to rank the alternatives. …The main advantage of the proposed method is that it not only considers the distance measure from the point view of algebra and geometry but also overcomes the disadvantage of the existing cosine similarity measure. Finally, an example is provided to illustrate the feasibility of the proposed method and some comparative analyses are given to show its efficiency. Show more
Keywords: Hesitant fuzzy linguistic term set, similarity measure, distance measure, TOPSIS
DOI: 10.3233/JIFS-181886
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 995-1006, 2019
Authors: Panda, Banoj Kumar | Bhanja, Urmila | Pattnaik, Prasant Kumar
Article Type: Research Article
Abstract: In Mobile Adhoc Network (MANET), obstacles in terrain and nodes mobility are main constrains due which performance degrades. To mitigate these effects, the routing protocol should be mobility and obstacles aware. In this work, we proposed a novel Obstacle and Mobility Aware Routing (OMAR) protocol. In OMAR, for obstacles avoidance, DeCasteljau Algorithm based on Bezier curve is been used. And to reduce effects of mobility and energy shortage of a node, an Energy based Mobility Index (EMI) routing scheme is been developed. The path possesses high EMI is selected as route. The performance of proposed Mobility and Obstacle Aware Routing …protocol is evaluated using NS2 simulator. Simulation results show that the proposed algorithm reduces energy consumption, overhead, delay and increases data delivery in the network. Show more
Keywords: Obstacle awareness, mobility awareness, link duration, Bezier curve, obstacle
DOI: 10.3233/JIFS-181917
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1007-1017, 2019
Authors: Anitha, G. | Vijayakumari, V.
Article Type: Research Article
Abstract: Improving network lifetime of Wireless Sensor Network (WSN) is the prime concern for researchers to enhance the monitoring duration and reducing risk due to automation. The node lifetime is mainly determined by - the number of bits transmitted and distance between the sender and receiver. The optimal selection of Cluster Head (CH) and relay node, avoids unnecessary loss of energy due to data sharing with long distance node. A Fuzzy logic based routing algorithm is designed to enhance the network lifetime by optimally selecting CH and relay node providing less number of bits transmitted. A threshold framework is designed to …reduce the number of handshake signals, the Cluster Member (CM) starts its connection establishment and shares data once the threshold is reached, thereby improving the lifetime. The proposed algorithm when compared with LEACH protocol exhibits that the improvement with respect to lifetime is 1.44 times and with respect to throughput it is 1.17 times. Since the algorithm takes the average energy of cluster in account, equal distribution of load is observed. The unequal clustering exhibited by the proposed algorithm proves its resistance over Energy Hole and HOT SPOT problems. Show more
Keywords: Wireless sensor network (WSN), energy hole, HOT SPOT and energy efficient
DOI: 10.3233/JIFS-181923
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1019-1031, 2019
Authors: Dokht Shakibjoo, Ali | Moradzadeh, Mohammad | Moussavi, Seyed Zeinolabedin | Afrakhte, Hossein
Article Type: Research Article
Abstract: Load frequency control (LFC) is one of the important control problems in design and operation of power systems as permanent deviation of frequency from nominal value affects power system operation and reliability. This paper presents a control method based on neural network for LFC of a two-area power system containing re-heat thermal plants. System parameters are assumed to be unknown and the proposed type-2 fuzzy controller is designed online, is adaptive and does not require initial adjustment by the operator. The training method of the type-2 fuzzy controller includes error back-propagation and gradient descent. In this paper, since the …dynamics of the system is unknown, it is modelled using multilayer perceptron (MLP) structure, and Jacobian of the system is extracted to determine system model. In order to evaluate the robustness of proposed online adaptive fuzzy type-2 controller (OADF) against parameter changes, a time-variant parameter is added to the system. The performance of the controller is compared with the PI, PID, N-PID, fuzzy-PI and neural network controllers. Simulation results illustrate the improved performance of LFC and its capability to overcome uncertain and time-variant parameters. Show more
Keywords: LFC, adaptive type-2 fuzzy control, multi-area power system, MLP, back-propagation and gradient descent
DOI: 10.3233/JIFS-181963
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1033-1042, 2019
Authors: Yan, Shuli | Liu, Sifeng | Zeng, Xiangyan
Article Type: Research Article
Abstract: A new dynamic multi-attribute group decision making method based on matrix grey target decision model is proposed. The attributes’ data of alternatives about decision makers in different stages are represented by matrices, and they are considered as performance values in 4-dimensional space. The best, worst attributes’ values in other 3-dimensions formed the new matrices, which are defined as expected bull’s-eye, unexpected bull’s-eye, and then the deviations of alternatives and expected, unexpected bull’s eye are presented using matrix norm. The alternatives are ranked by the deviations. Finally, the examples are provided to illustrate the proposed method.
Keywords: Dynamic multi-attribute group decision making, Matrix grey target model, 4-dimensional space, matrix norm
DOI: 10.3233/JIFS-181973
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1043-1053, 2019
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