Genetic learning and optimization of fuzzy sets in fuzzy rule-based system
Matheus Giovanni Pires, Heloisa A. Camargo · 2005
This work presents a comparative study of two genetic approaches to fuzzy systems generation, where the genetic algorithm is applied to the fuzzy sets. In the first approach a previously defined database is tuned considering a fixed rule base, and in the second one the database is generated through the GA with the posteriori definition of the rule base for each newly generated database. Experimental results are presented and discussed.