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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.

The dimension of a knowledge domain can impact the use of genetic algorithms to automatically design fuzzy rule bases, since the search space for the genetic algorithm increases exponentially with the number of features. Filters are a possible approach to reduce the number of features. However, the filter approach does not take into consideration the particular aspects of fuzzy logic when selecting or ranking features. This work presents a method for feature subset selection using the Wang & Mendel method as the base for a wrapper. Experimental results are presented and discussed.