A cooperative coevolutionary algorithm for jointly learning fuzzy rule bases and membership functions

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 components (mainly the rule base and the data base). Instead, we propose a simultaneous derivation process to properly consider their dependency. Since the problem complexity rises, the proposed method will be based on a cooperative coevolutionary algorithm.

• Type: Conference
• Year: 2001
• Where: EUSFLAT
• Authors: Jorge Casillas, Oscar Cordón, Francisco Herrera
• Keywords: EUSFLAT 2001, EUSFLAT 2007, Fuzzy Rule-based System, Knowledge Base, Simultaneous Derivation Process