Fuzzy rule extraction by bacterial memetic algorithms

Authors:
J. Botzheim;C. Cabrita;L. T. Kóczy;A. E. Ruano
Affiliations:
Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary and Faculty of Engineering Sciences, Széchenyi István Universit ...;Center for Intelligent Systems, University of Algarve, Faro, Portugal;Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary and Faculty of Engineering Sciences, Széchenyi István Universit ...;Center for Intelligent Systems, University of Algarve, Faro, Portugal
Venue:
International Journal of Intelligent Systems
Year:
2009

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Abstract

In our previous papers, fuzzy model identification methods were discussed. The bacterial evolutionary algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg–Marquardt method was also proposed for determining membership functions in fuzzy systems. The combination of the evolutionary and the gradient-based learning techniques is usually called memetic algorithm. In this paper, a new kind of memetic algorithm, the bacterial memetic algorithm, is introduced for fuzzy rule extraction. The paper presents how the bacterial evolutionary algorithm can be improved with the Levenberg–Marquardt technique. © 2009 Wiley Periodicals, Inc.