IF–THEN rules generation based on fuzzy relational equations and genetic algorithm

Abstract

An approach to IF-THEN rules generation by solving fuzzy relational equations, which allows avoiding rules selection from the set of candidate rules, is suggested in this paper. The system of fuzzy rules can be rearranged as a collection of linguistic solutions of fuzzy relational equations using the composite system of fuzzy terms. Resolution of fuzzy relational equations using the genetic algorithm guarantees the optimal number of fuzzy rules for each output fuzzy term and the optimal geometry of input fuzzy terms for each linguistic solution.