By Topic

Multi-deme evolutionary algorithm based approach to the generation of fuzzy systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
6 Author(s)
Rojas, I. ; Dept. of Archit. & Comput. Technol., Granada Univ., Spain ; Pomares, H. ; Gonzalez, J. ; Gloesekotter, P.
more authors

In this paper we propose a genetic algorithm (GA) that is capable of simultaneously optimizing the structure of the system and tuning the parameters that define the fuzzy system. For this purpose, we use the concept of multiple-deme GAs, in which several populations with different structures (number of input variables) evolve and compete with each other. In each of these populations, the element also has different numbers of membership functions in the input spaces and different numbers of rules. Instead of the normal coding system used to represent a fuzzy system, in which all the parameters are represented in vector form, we performed coding by means of multidimensional matrices, in which the elements are real-valued numbers, rather than the traditional binary or gray coding

Published in:

Fuzzy Systems, 2001. The 10th IEEE International Conference on  (Volume:3 )

Date of Conference: