• DocumentCode
    3304251
  • Title

    Mutually-inversistic rough fuzzy logic

  • Author

    Xunwei Zhou

  • Author_Institution
    Inst. of Inf. Technol., Beijing Union Univ., Beijing, China
  • Volume
    1
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    382
  • Lastpage
    385
  • Abstract
    Mutually-inversistic rough fuzzy logic is the integration of mutually-inversistic fuzzy logic constructed by the author and rough fuzzy sets. Mutually-inversistic fuzzy logic can be used to mine fuzzy association rules on the finer granule objects, while mutually-inversistic rough fuzzy logic can be used to mine fuzzy association rules on the coarser granule equivalence classes.
  • Keywords
    data mining; fuzzy logic; granular computing; rough set theory; fuzzy association rule mining; granule equivalence class; mutually inversistic rough fuzzy logic; rough fuzzy sets; Approximation methods; Association rules; Employment; Fuzzy logic; Fuzzy sets; Materials; Rain; fuzzy association rule mining of the lower and upper approximations of equivalence classes; granular computing; mutually-inversistic fuzzy logic; mutually-inversistic rough fuzzy logic; rough fuzzy sets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-61284-180-9
  • Type

    conf

  • DOI
    10.1109/FSKD.2011.6019505
  • Filename
    6019505
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3304251