Fuzzy Rules Generation using Genetic Algorithms with Self-adaptive Selection

Abstract

The definition of the Rule Base is one of the most important and difficult tasks when designing Fuzzy Systems. A method for the generation of fuzzy rule bases using genetic algorithm, including a phase of preselection of candidate rules, has been proposed by the authors. The selection of candidate rules uses criteria based on heuristics related to the degree of coverage of the rules. This paper proposes the use of a self-adaptive algorithm for the fitness calculation in the genetic algorithm, as an improvement of the referred method. The algorithm proposed emphasises the usefulness of compact rule bases as a means of transparency enhancement. Some experiment results are presented with a brief discussion of the advantages of the proposal.