• DocumentCode
    1519806
  • 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
  • Volume
    9
  • Issue
    4
  • fYear
    2001
  • fDate
    8/1/2001 12:00:00 AM
  • Firstpage
    667
  • Lastpage
    674
  • 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;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/91.940977
  • Filename
    940977
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1519806