Optimization of Fuzzy If-Then Rule Bases by Evolutionary Tuning of the Operations

Abstract

This paper discusses optimization of fuzzy if-then rule bases by an evolutionary adjustment of the operations considered to use the rules. Adjustment of the operations is made by first parameterizing the operations with the help of either a contracting function or an order automorphism, followed by evolutionary tuning of the parameters. Optimization of a system based on Takagi-Sugeno rules and its distributed implementation are discussed in detail.