Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

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: Hussain, Azmat | Irfan Ali, Muhammad | Mahmood, Tahir

Article Type: Research Article

Abstract: In this manuscript we develop a comprehensive model to tackle decision making problems where strong points of view are in the favor and against some projects, entities or plans. Therefore a new approach is adopted to hybrid q-rung orthopair fuzzy sets with notions of covering rough set and TOPSIS. This model has stronger capability than intuitionistic fuzzy set and Pythagorean fuzzy set to manage the uncertainty. Furthermore an example is given to demonstrate how the proposed method helps us in decision making problems.

Keywords: Fuzzy sets, q-rung orthopair fuzzy sets, q-rung orthopair fuzzy β-covering, q-rung orthopair fuzzy β-covering neighborhoods, covering based q-rung orthopair fuzzy rough set, q-rung orthopair fuzzy TOPSIS methodology

DOI: 10.3233/JIFS-181832

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 981-993, 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