Fuzzy rule extraction by bacterial memetic algorithms

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

http://hdl.handle.net/10400.1/2306

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
IFSA2005.pdf		377.39 KB	Adobe PDF	Download

Send Feedback

Authors

Botzheim, J.

Cabrita, Cristiano Lourenço

Ruano, Antonio

Kóczy, László T.

Abstract(s)

In our previous papers fuzzy model identification methods were discussed. The bacterial 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 will be called bacterial memetic algorithm. In this paper this new kind of memetic algorithm is introduced for fuzzy rule extraction. The paper presents how the bacterial algorithm can be improved with the Levenberg-Marquardt technique.

Keywords

Bacterial algoritm Levenberg-Marquardt method Memetic algorithm

URI

http://hdl.handle.net/10400.1/2306

Citation

Botzheim, J.; Cabrita, C.; Ruano, A. E.; Koczy, Laszlo T. Fuzzy Rule Extraction by Bacterial Memetic Algorithms, Trabalho apresentado em IFSA 2005 World Congress, In Proceedings of the IFSA 2005 World Congress, Beijing, 2005.