Evolutionary Local Search of Fuzzy Rules through a Novel Neuro-Fuzzy Encoding Method
Alberto Carrascal, Daniel Manrique, José Ríos, Cláudio Rossi · Evolutionary Computation · 2003
This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.