Journal of Intelligent & Fuzzy Systems - Volume 27, issue 5

Authors: Mohtashami, Ali

Article Type: Research Article

Abstract: This paper proposes a novel meta-heuristic based algorithm which provides the optimal solution for several different degrees of feasibility for fuzzy linear and nonlinear programming problems. The proposed method has got the ability for solving those problems in which all coefficients of the objective function and constraints are represented by LR fuzzy numbers with linear and/or non-linear membership function. To solve the fuzzy problems, this paper provides a new hybrid genetic algorithm accompanied by a new proposed method of simulating fuzzy coefficients which 1) eliminates the need of applying defuzzification methods and/or expected interval methods, and 2) allows dealing with …different types of fuzzy numbers, properly. In order to show the performance of the proposed method, it is compared with “M. Jiménez, M. Arenas, A. Bilbao and M.V. Rodríguez, Linear programming with fuzzy parameters: An interactive method resolution, European Journal of Operational Research 177 (2007), 1599–1609.”. Computational results reveal that the proposed method is superior to the Jiménez et al. [13] method from the viewpoint of feasibility and optimality. Show more

Keywords: Genetic algorithm, fuzzy linear programming, fuzzy non-linear programming, fuzzy number, hybrid genetic algorithm (HGA)

DOI: 10.3233/IFS-141234

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2611-2622, 2014

Authors: Azadbakht, Bakhtiar | Zolata, Hamidreza | Khayat, Omid

Article Type: Research Article

Abstract: Neuro-muscular and musculoskeletal disorders and injuries highly affect the life style and the motion abilities of an individual. The primary purpose of this work is to develop a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. To this aim, the EMG signals of five skeletal muscles as biceps, deltoid, triceps, tibialis anterior and quadriceps muscles are recorded in three states of isometric contraction (ISO), maximum voluntary contraction (MVC) and dynamic contraction from 22 normal subjects aged between 20 and 30 half of them are male. Totally, 14 combinatory extracted features are analyzed …to find which of them or a combinatory set of them are discriminative and selective for muscle force quantification and classification. The neuro-fuzzy system is trained with 70 percent of the recorded EMG cut off windows and then it is employed for classification and modeling purposes. For each muscle the most effective extracted features are found for males and females separately by a reference classifier. In the experiments, after the optimum set of combinatory features is found by a reference classifier, the neuro-fuzzy classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Then, different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used. Show more

Keywords: EMG signal characterization, neuro-fuzzy classifier, contraction states, feature extraction

DOI: 10.3233/IFS-141235

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2623-2634, 2014

Authors: Kannan, P. | Shantha Selva Kumari, R.

Article Type: Research Article

Abstract: VLSI architecture for face recognition system based on Local Gabor XOR Pattern (LGXP) feature extraction method is presented in this paper. LGXP is utilized to encode Gabor phase variations and to extract feature with the help of Gabor filter and Local XOR Pattern (LXP) operator. VLSI architecture for Gabor Filter and a Behavioral model for LXP operator for feature extraction are investigated. Also a behavioral model for Similarity matching is designed using Verilog language. The similarity matching for face recognition is executed by L1 distance measure. Therefore our approach explores the effectiveness of Gabor phase information on FPGA platform by …addressing the drawbacks like computational complexity and hardware complexity by mapping the algorithms. The proposed approach is designed on virtex-5 device using Veriolg HDL in Xilinx ISE tool and the logic utilization results will be generated using synthesis tool while the power consumption report will be analyzed using Xpower analysis tool. Also the effectiveness of our design is evaluated with FAR, FRR and accuracy plot in Matlab simulation environment. Research outcome of our proposed face recognition system over UPC face database is 72.225% Accuracy for distance matching threshold of ‘5’. Show more

Keywords: VLSI architecture, LGXP, gabor filter, LXP, similarity matching, L1 distance

DOI: 10.3233/IFS-1412366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2635-2647, 2014

Authors: Maheswari, R.V. | Subburaj, P. | Vigneshwaran, B. | Kalaivani, L.

Article Type: Research Article

Abstract: Partial discharge (PD) is an important tool for assessing the quality of the insulation system in High Voltage (HV) power apparatus. In this work, four different PD sources namely corona and surface discharges in both air and oil are measured in the HV laboratory. Initially 3-D (�-q-n) PD patterns are extracted from the PD data. Then it is subjected to two different fractal image compression techniques namely box counting method and semi variance method. For box counting method, the fractal dimensions like fractal dimension average, standard deviation and lacunarity are evaluated. For semi variance method, horizontal and vertical fractal dimension …averages are evaluated. The extracted fractal features from 3-D PD patterns are used as input parameters for non linear Support Vector Machine (SVM) for PD recognition. The performance of non linear SVM is compared with Artificial Neural Network (ANN) and linear SVM classifiers. The non linear SVM with semi variance method provides outer performance as compared with other methods due to its gain flexibility and good out-of-sample generalization. Show more

Keywords: Partial discharge (PD), fractal image compression techniques, artificial neural network (ANN), affine transformation (AT), support vector machine (SVM)

DOI: 10.3233/IFS-141237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2649-2664, 2014

Authors: Liang, Cheng-Yu | Shi, Fu-Gui

Article Type: Research Article

Abstract: In this paper, the degrees to which a mapping is continuous, open or closed are introduced in (L, M)-fuzzy topological spaces by using implication operation and some characterizations of them are presented. Also their relationships with the degrees of compactness, connectedness, T1 and T2 axioms in (L, M)-fuzzy topological spaces are discussed.

Keywords: (L, M)-fuzzy topological space, continuous mapping, open mapping, closed mapping, homeomorphism

DOI: 10.3233/IFS-141238

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2665-2677, 2014

Authors: Zhou, Wei | Meng, Sun | Chen, Minghui

Article Type: Research Article

Abstract: This study proposes the hybrid Atanassov intuitionistic fuzzy number (HAIFN) to effectively and accurately represent membership and non-membership degrees in an Atanassov's intuitionistic fuzzy environment. The HAIFN is obtained by combining the crisp number with the interval-valued number, in which decision makers provide only an interval-valued membership degree, thereby avoiding the intricate and difficult evaluation of the non-membership degree. Based on the HAIFN, the hybrid Atanassov intuitionistic fuzzy Bonferroni mean and the generalized hybrid Atanassov intuitionistic fuzzy Bonferroni mean are introduced to aggregate the hybrid Atanassov intuitionistic fuzzy information and capture their interrelationship. The hybrid Atanassov intuitionistic fuzzy weighted Bonferroni …mean, the generalized hybrid Atanassov intuitionistic fuzzy weighted Bonferroni mean, and their desired properties are further investigated given the distinct importance of each criterion. A practical case is provided at the end to demonstrate the application of the proposed fuzzy numbers and aggregation operators. Show more

Keywords: Hybrid Atanassov intuitionistic fuzzy number, Bonferroni mean, fuzzy sets, multi-criteria aggregation

DOI: 10.3233/IFS-141239

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2679-2690, 2014

Authors: Zhang, Jingyu | Zhou, Jian | Zhong, Shuya

Article Type: Research Article

Abstract: An inverse minimum spanning tree problem is to make the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, a type of fuzzy inverse minimum spanning tree problem is introduced from a LAN reconstruction problem, where the weights of edges are assumed to be fuzzy variables. The concept of fuzzy α-minimum spanning tree is initialized, and subsequently a fuzzy α-minimum spanning tree model and a credibility maximization model are presented to formulate the problem according to different decision criteria. In order to …solve the two fuzzy models, a fuzzy simulation for computing credibility is designed and then embedded into a genetic algorithm to produce some hybrid intelligent algorithms. Finally, some computational examples are given to illustrate the effectiveness of the proposed algorithms. Show more

Keywords: Minimum spanning tree, inverse optimization, fuzzy programming, genetic algorithm

DOI: 10.3233/IFS-141384

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 5, pp. 2691-2702, 2014