• DocumentCode
    3026866
  • Title

    Combinations of evolutionary algorithms and fuzzy systems: a survey

  • Author

    Shi, Yuhui

  • Author_Institution
    EDS Indianapolis Technol. Center, Carmel, IN, USA
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    610
  • Lastpage
    614
  • Abstract
    Lot of schemes to combine evolutionary algorithms and fuzzy systems have been reported in the literature in recent years. Evolutionary algorithms have been used to design fuzzy systems and fuzzy systems have been utilized to adapt the evolutionary algorithms. Both sides interact with each other both supportively and collaboratively. We provide a survey with focus on evolutionary algorithms as supporting tools for designing fuzzy systems since this is the main research work reported in the literature. The survey is organized from three perspectives: homogeneous vs. heterogeneous representation; online learning vs. offline learning; static learning vs. adaptive learning algorithms
  • Keywords
    evolutionary computation; fuzzy systems; knowledge representation; learning (artificial intelligence); adaptive learning algorithms; evolutionary algorithms; fuzzy systems design; heterogeneous representation; offline learning; online learning; static learning; Algorithm design and analysis; Collaboration; Collaborative work; Dynamic range; Evolutionary computation; Fuzzy systems; Genetic mutations; Heuristic algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
  • Conference_Location
    New York, NY
  • Print_ISBN
    0-7803-5211-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.1999.781766
  • Filename
    781766