Fuzzy rule extraction by bacterial memetic algorithms

Publication Name: International Journal of Intelligent Systems

Publication Date: 2009-03-01

Volume: 24

Issue: 3

Page Range: 312-339

Description:

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.

Open Access: Yes

DOI: 10.1002/int.20338

Authors - 4