Title :
Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base
Author :
Cordón, Oscar ; Herrera, Francisco ; Villar, Pedro
Author_Institution :
Dept. of Comput. Sci. & Artificial Intelligence, Granada Univ., Spain
fDate :
8/1/2001 12:00:00 AM
Abstract :
A method is proposed to automatically learn the knowledge base by finding an appropiate data base by means of a genetic algorithm while using a simple generation method to derive the rule base. Our genetic process learns the number of linguistic terms per variable and the membership function parameters that define their semantics, while a rule base generation method learns the number of rules and their composition
Keywords :
fuzzy systems; genetic algorithms; knowledge based systems; learning (artificial intelligence); fuzzy rule-based system; genetic learning; genetic process; knowledge base generation; linguistic terms; membership function parameters; rule base generation method; Artificial intelligence; Computer science; Concrete; Fuzzy systems; Genetic algorithms; Helium; Hybrid power systems; Knowledge based systems; Learning; System performance;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
