Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30184
Using Swarm Intelligence for Improving Accuracy of Fuzzy Classifiers

Authors: Hassan M. Elragal

Abstract:

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on Takagi- Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the proposed fuzzy classifiers including premise (antecedent) parameters, consequent parameters and structure of fuzzy rules are optimized using PSO. Experimental results show that higher classification accuracy can be obtained with a lower number of fuzzy rules by using the proposed PSO fuzzy classifiers. The performances of M_PSO and TS_PSO fuzzy classifiers are compared to other fuzzy based classifiers

Keywords: Fuzzy classifier, Optimization of fuzzy systemparameters, Particle swarm optimization, Pattern classification.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1055327

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1913

References:


[1] Yager, R. R. and Filev, D. P. "Essentials of Fuzzy Modeling and Control," John Wiley, New York, U.S.A. (1994).
[2] Jang, J. S., Sun, C. T. and Mizutani, E., " Neuro-Fuzzy and Soft Computing," Prentice Hall, New Jersey, U.S.A. (1997).
[3] J.C. Bezdek, "Pattern Recognition with Fuzzy Objective Function Algorithm," Plenum Press, New York, 1981.
[4] J.C. Bezdek, "On the relationship between neural networks, pattern recognition and intelligence," Int. J. Approx. Reasoning 6 (2) (1992) 85- 107.
[5] C.T. Lin, C.S.G. Lee, "Neural network-based fuzzy logic control and decision system," IEEE Trans. Comput. 40 (12) (1991) 1320-1336.
[6] C.F. Juang, J.Y. Lin, C.T. Lin, "Genetic reinforcement learning through symbiotic evolution for fuzzy controller design," IEEE Trans. Syst. Man Cybern. Part B 30 (2) (2000) 290-302.
[7] C.L. Karr, "Design of an adaptive fuzzy logic controller using a genetic algorithm," Proceedings of the Fourth International Conference on Genetic Algorithm, San Diego, July 12-16, 1991, pp. 450-457.
[8] C.L. Karr, E.J. Gentry, "Fuzzy control of pH using genetic algorithm," IEEE Trans. Fuzzy Systems. 1 (1) (1993) 46-53.
[9] M. Setnes, H. Roubos, "GA-Fuzzy modeling and classification: complexity and performance," IEEE Trans. Fuzzy Systems. 8 (4) (2000) 509-522.
[10] Mahamed G.H. Omran, Andries P Engelbrecht, and Ayed Salman, "Dynamic Clustering using Particle Swarm Optimization with Application in Unsupervised Image Classification," Proceeding of world academy of science. Engineering and technology, volume 9, November 2005 ISSN 1307-6884.
[11] Chia-Chong Chen "Design of PSO-based Fuzzy Classification Systems", Tamkang Journal of Science and Engineering," Vol. 9, No 1, (2006) pp. 63_70
[12] Ishibuchi, H., Nozaki, K., Yamamoto, N. and Tanaka, H., "Selecting Fuzzy If-Then Rules for Classification Problems Using Genetic Algorithms," IEEE Trans. Fuzzy Systems, Vol. 3, (1995) pp. 260_270.
[13] Jang, J. S., "ANFIS: Adaptive-Network-Based Fuzzy Inference systems," IEEE Trans. on Systems, Man and Cybernetics, Vol. 23, (1993) pp. 665_685.
[14] Nozaki, K., Ishibuchi, H. and Tanaka, H., "Adaptive Fuzzy Rule-Based Classification Systems," IEEE Trans. on Fuzzy Systems, Vol. 4, No. 3, Aug., (1996) pp. 238_250.
[15] Wang, L. X. and Mendel, J. M., "Generating Fuzzy Rules by Learning from Examples," IEEE Trans. On Systems, Man and Cybernetics, Vol. 22, (1992) pp. 1414_ 1427.
[16] Wong, C. C. and Chen, C. C., "A GA-Based Method for Constructing Fuzzy Systems Directly from Numerical Data," IEEE Trans. on Systems, Man and Cybernetics- Part B: Cybernetics, Vol. 30, (2000) pp. 904_911.
[17] Simpson, P. K., "Fuzzy Min-Max Neural Networks- Part 1: Classification," IEEE Trans. Neural Networks, Vol. 3, Sep., (1992) pp. 776_786.
[18] Wong, C. C. and Chen, C. C., "A Hybrid Clustering and Gradient Descent Approach for Fuzzy Modeling," IEEE Trans. on Systems, Man and Cybernetics-Part B: Cybernetics, Vol. 29, (1999) pp. 686_693.
[19] Xie, X.L., and G.Beni, "A validity measure for fuzzy clustering," IEEE trans. Pattern Anal. Mach. Intell. 3(8): 1991 pp. 841-846.
[20] S. L. Chiu, "Fuzzy Model Identification Based on Cluster Estimation," Journal of Intelligent and Fuzzy Systems, 1994 pp. 267-278,.
[21] Emami, M.R. Turksen, Burhan. Goldenberg A.A.,. "Development of A Systematic Methodology of Fuzzy Logic Modeling," IEEE transaction on Fuzzy Systems, 6(3) 1998.
[22] Salehfar, H. et al., "A systematic approach to linguistic fuzzy modeling based on input-output data," IEEE Proceedings of the 2000 Winter Simulation Conference, 2000.
[23] Vachkov, G. and Fukuda, T. , "Multilevel composite fuzzy models," The Ninth IEEE International Conference on Fuzzy Systems Volume 1, Issue , 2000 pp. 453 - 458.
[24] Hwang, H.S., "Automatic design of fuzzy rule base for modeling and control using evolutionary programming," IEE Proc-Control Theory Appl, Vol 146, 1999.
[25] A. Homaifar, E. McCormick, "Simultaneous design of membership functions and rule sets for fuzzy controller using genetic algorithms," IEEE Trans. Fuzzy Systems. 3 (2) (1995) 129-139.
[26] O. Cordon, F. Herrera, P. Villar, "Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base," IEEE Trans. Fuzzy Systems. 9 (4) (2001) 667-674.
[27] S.Y. Ho, H.M. Chen, S.J. Ho, T.K. Chen, "Design of accurate classifiers with a compact fuzzy-rule base using an evolutionary scatter partition of feature space," IEEE Trans. Syst. Man Cybern. Part B 34 (2) (2004) 1031-1044.
[28] Enwang Zhou, Alireza Khotanzad, "Fuzzy classifier design using genetic algorithms", Pattern Recognition 40 (2007) 3401 - 3414.
[29] Tanya Mirzayans, Nitin Parimi, Patrick Pilarski, Chris Backhouse,Loren Wyard-Scott, Petr Musilek , "A Swarm Based System for Object Recognition," Neural Network World 3/05, 2005, pp. 243-255.
[30] Ata E. Zadeh Shermeh and Reza Ghaderi, "An Intelligent System for Classification of the Communication Formats Using PSO," Informatica 32 (2008) pp. 213-218.
[31] Mamdani, E.H. and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller," International Journal of Man-Machine Studies, Vol. 7, No. 1, 1975 pp. 1-13.
[32] Sugeno, M., Industrial applications of fuzzy control, Elsevier Science Pub. Co., 1985.
[33] James Kennedy and Russell C. Eberhart, "Swarm Intelligence", Morgan Kaufmann Publishers, 2001.
[34] Mahamed G. H. Omran, "Particle Swarm Optimization Methods for Pattern Recognition and Image Processing", PhD. thesis , University of Pretoria, Pretoria, South Africa, November, 2004.
[35] Kennedy, J. and Eberhart, R., "Particle Swarm Optimization," Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia (1995), 1942-1945.
[36] R. Forrest, " Genetic Algorithms: Principles of Natural Selection Applied to Computation," Science, Vol. 261, pp. 872-878, 1993.
[37] R. Storn and K. Price. Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11:341-359, 1997.