Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base

Abstract

A method is proposed to automatically learn the knowledge base by finding an appropiate data base by means of a genetic algorithm while using a simple generation method to derive the rule base. Our genetic process learns the number of linguistic terms per variable and the membership function parameters that define their semantics, while a rule base generation method learns the number of rules and their composition.