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