Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2237
Título: Fuzzy rule extraction by bacterial memetic algorithms
Autor: Botzheim, J.
Cabrita, Cristiano Lourenço
Kóczy, László T.
Ruano, A. E.
Data: 2009
Citação: 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.
Resumo: 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.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2237
DOI: http://dx.doi.org710.1002/int.20338
ISSN: 08848173
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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