• DocumentCode
    2491571
  • Title

    Fuzzy modeling method based on data mining

  • Author

    Wang, Yongfu ; Zhao, Hong ; Liu, Jiren ; Chai, Tianyou

  • Author_Institution
    Sch. of Mech. Eng. & Autom., Univ. of Northeastern, Shenyang
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    5223
  • Lastpage
    5227
  • Abstract
    Aiming at WM method lacking of completeness and robustness, which was presented by Lixin Wang, fuzzy system is set up by data mining in this paper. Rules base and fuzzy system produced by data mining can ergodic all the fuzzy subspace, which insures the completeness of rules base. Otherwise, rules produced by data mining are elected out in the whole sample data, but WM method is a result only from a certain datum. So, data mining has better robustness and simulation results show its validity.
  • Keywords
    data mining; fuzzy systems; knowledge based systems; data mining; fuzzy modeling; fuzzy system; rule based system; Association rules; Automation; Data mining; Databases; Fuzzy logic; Fuzzy sets; Fuzzy systems; Hybrid power systems; Mathematical model; Robustness; Fuzzy logic system; completeness; data mining; fuzzy rules; modelling; robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593779
  • Filename
    4593779