Paper Info
Title
Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base
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
Year
DOI
Venue
2001
10.1109/91.940977
IEEE T. Fuzzy Systems
Keywords
DocType
Volume
computer science,fuzzy systems,artificial intelligence,concrete,genetic algorithm,indexing terms,knowledge base,knowledge based systems,rule based,membership function,genetic algorithms,system performance,genetics,helium,learning artificial intelligence
Journal
9
Issue
ISSN
Citations 
4
1063-6706
110
PageRank 
References 
Authors
4.16
22
3
Search Limit
100110
Name
Order
Citations
PageRank
O. Cordón1138066.74
Francisco Herrera2273911168.49
P. Villar31104.16