Fuzzy rule extraction by bacterial memetic algorithms

J. Botzheim, C. Cabrita, L. T. Kóczy, A. E. Ruano

Research output: Contribution to journalArticle

33 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)312-339
Number of pages28
JournalInternational Journal of Intelligent Systems
Volume24
Issue number3
DOIs
Publication statusPublished - Mar 1 2009

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

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