A cooperative coevolutionary algorithm for jointly learning fuzzy rule bases and membership functions.
Jorge Casillas, Óscar Cordón, Francisco Herrera · 2001
When a whole knowledge base must be derived for a fuzzy rule-based system, learning methods usually address this task with two or more sequential stages by separately designing each of its com-ponents (mainly the rule base and the data base). Instead, we propose a si-multaneous derivation process to prop-erly consider their dependency. Since the problem complexity rises, the pro-posed method will be based on a coop-erative coevolutionary algorithm.