Fuzzy rule extraction by bacterial memetic algorithms

Botzheim, J.; Cabrita, Cristiano Lourenço; Kóczy, László T.; Ruano, Antonio

http://hdl.handle.net/10400.1/2237

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Authors

Botzheim, J.

Cabrita, Cristiano Lourenço

Kóczy, László T.

Ruano, Antonio

Abstract(s)

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.

URI

http://hdl.handle.net/10400.1/2237

Citation

Botzheim, J.; Cabrita, C.; Kóczy, L. T.; Ruano, A. E. Fuzzy rule extraction by bacterial memetic algorithms, International Journal of Intelligent Systems, 24, 3, 312-339, 2009.