Data Driven Fuzzy Modeling for Sugeno and Mamdani Type Fuzzy Model using Memetic Algorithm

Автор: Savita Wadhawan, Gunjan Goel, Srikant Kaushik

Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs

Статья в выпуске: 8 Vol. 5, 2013 года.

Бесплатный доступ

The process of fuzzy modeling or fuzzy model identification is an arduous task. This paper presents the application of Memetic algorithms (MAs) for the identification of complete fuzzy model that includes membership function design for input and output variables and rulebase generation from the numerical data set. We have applied the algorithms on four bench mark data: A rapid Ni-Cd battery charger, the Box & Jenkins’s gas-furnace data, the Iris data classification problem and the wine data classification problem. The comparison of obtained results from MAs with Genetic algorithms (GAs) brings out the remarkable efficiency of MAs. The result suggests that for these problems the proposed approach is better than those suggested in the literature.

Еще

Memetic Algorithms (MAs), Genetic Algorithms (GAs ), Fuzzy Modeling, Fuzzy Systems

Короткий адрес: https://sciup.org/15011937

IDR: 15011937

Список литературы Data Driven Fuzzy Modeling for Sugeno and Mamdani Type Fuzzy Model using Memetic Algorithm

G. J. Klir and B. Yuan, “Fuzzy Sets and Fuzzy Logic—Theory and Applications”, Englewood Cliffs, NJ: Prentice-Hall, 1995.
L. A. Zadeh, “Fuzzy logic and approximate reasoning,”, Syntheses, vol. 30, pp. 407–428, 1975.
Goldberg DE, “Genetic algorithms in search, optimization and machine learning. Reading”, MA: Addison-Wesley Publishing Co; 1989.
Hegazy T., “Optimization of construction time-cost trade-off analysis using genetic algorithms”, Can J Civil Eng 26: 685–97, 1999.
Al-Tabtabai H, Alex PA. “Using genetic algorithms to solve optimization problems in construction”, Eng Constr Archit Manage ;6(2):121–32,1999.
Joglekar A, Tungare M., “Genetic algorithms and their use in the design of evolvable hardware”, http://www.manastungare.com/articles/genetic/geneticalgorithms.pdf; 2003, accessed on,15 pp.,May 20,2004.
P. Merz and B. Freisleben, “Fitness landscapes and memetic algorithm design”, in New Ideas in Optimization, D. Corne, M. Dorigo, and F. Glover, Eds. London, U.K.: McGraw-Hill, 1999.
A. Kolen and E. Pesch, “Genetic local search in combinatorial optimization”, Discrete Applied Mathematics and Combinatorial Operations Research and Computer Science, vol. 48, pp. 273–284, 1994.
Dawkins R. The selfish gene. Oxford: Oxford University Press; 1976.
Merz P, Freisleben B. “A genetic local search approach to the quadratic assignment problem”, In: Ba¨ck CT, editor. Proceedings of the 7th international conference on genetic algorithms. San Diego, CA: Morgan Kaufmann; pp. 465–72, 1997.
P. Moscato, “On evolution, search, optimization, genetic algorithms and martial arts: Toward memetic algorithms”, Caltech Concurrent Computation Program, California Institute of Technology, Pasadena, Tech. Rep. 790, 1989.
P. Moscato and M. G. Norman, “A memetic approach for the traveling salesman problem implementation of a computational ecology for combinatorial optimization on message-passing systems”, in Parallel Computing and Transputer Applications, M. Valero, E. Onate, M. Jane, J. L. Larriba, and B. Suarez, Eds. Amsterdam, The Netherlands: IOS Press, pp. 177–186,1992.
Emad Elbeltagi, Tarek Hegazy, Donald Grierson, “Comparison Among Five Evolutionary-Based Optimization Algorithms”, Advance Engineering Informatics ELSEVIER, vol. 19, pp. 43-53, 2005.
Khosla, A., Kumar, S., & Aggarwal, K.K. “Design and development of RFC-10: A Fuzzy Logic Based Rapid Battery Charger for Nickel-Cadmium Batteries.” HiPC(High Performance Computing) workshop on soft computing, Bangalore, pp 9-14, 2002.
http://www.research.4t.com
Linden, D. (Editor-in-Chief) Handbook of Batteries. McGraw Hill Inc., 1995.
Arun Khosla, Shakti Kumar, K.K.Aggarwal, Jagatpreet Singh, “ Particle Swarm Optimizer For Building Fuzzy Models”, Proceeding of one week workshop on applied soft computing SOCO-2005, Haryana Engg. College,Jagadhri,India , July 25-30, pp 43-71,2005.
]M. Sugeno, T.A. Yasukawa, “ A fuzzy logic based approach to qualitative modeling”, IEEE Trans. Fuzzy syst. 31, pp. 7-31, 1993.
R.M. tong, “The evaluation of fuzzy models derived from experimental data”, Fuzzy sets and systems, vol. 4, pp. 1-12,1980.
Witold Pedrycz, “An Identification Algorithm In Fuzzy Relational Systems”, Fuzzy Sets And Systems, Vol 13, pp. 153-167, 1984.
Chen-Wei Xu and yong-Zai Lu, “Fuzzy Model Identification And Self Learning For Dynamic Systems”, IEEE Trans. On Systems, Man And Cybernatics, Vol. Smc-17, pp. 683-689,1987.
Michio Sugeno and Takahiro Yasukawa, “ Linguistic Modeling Based On Numerical Data”, Proc. Of IFSA’91, Brussel,1991.
Y. Shi, R. Eberhart, and Y. Chen, “Implementation Of Evolutionary Fuzzy Systems”, IEEE Trans. Fuzzy Syt., Vol 7, pp. 109-119, Apr. 1999.
J.C. Bezdek, J.M. Keller, R. Krishnapuram, L. I. Kuncheva, and N.R. Pal, “Will The Real Iris Data Please Stand Up?”, IEEE Trans. Fuzzy Syst., Vol. 7, pp. 368-369, June 1999.
H. Ishibuchi and T. nakashima, “Voting In Fuzzy Rule-Based Systems For Pattern Classification Problems”, Fuzzy Sets And Syst., Vol. 103, pp. 223-238, 1999.
J.C. Bezdek, T. R. Reichherzer, G.S. Lim, and Y. Attokiouzel, “Multiple-Prototype Classifier Design,” IEEE Trans. Syst., Man, Cybern., Vol. 28, pp. 67-79, Feb, 1998.
Hartmut Surmann and Alexander Selenschtschikow, “Automatic Generation of Fuzzy Logic Rule Bases: Examples I”, Proc. Of The NF2002: First International ICSC Conference on Neuro-Fuzzy Technologies, pp 75, CUBA 16-19 Jan.2002.
Magne Setnes and Hans Roubos, “GA – Fuzzy Modeling and Classification: Complexity and Performance”, IEEE Trans. On Fuzzy Syst., Vol. 8, No. 5, October 2000.

Еще

Статья научная