• DocumentCode
    3479607
  • Title

    The Algorithm of Grid Clustering Based on Fuzzy Rough Set & its Application

  • Author

    Yuke Wei ; Jiangping Li ; Renhuang Wang

  • Author_Institution
    Fac. of Comput., Guangdong Univ. of Technol., Guangzhou
  • fYear
    2008
  • fDate
    12-14 Oct. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Traditional Chinese medicine (TCM) tongue diagnosis system is a big, complex one, its data is of great amount and many types, also the data cluster has uncertainty. In this article, the author introduced an advanced algorithm of grid clustering based on fuzzy rough set on the basis of analyzing the theory of fuzzy rough set. The algorithm has been put into use in rules mining of TCM tongue diagnosis system. The first step was grid dividing, to form basis data cluster formation, then provided truly data information in defining membership function. The membership function considered many elements that may influence cluster formation. The algorithm speeded up cluster by fuzzy grid dividing, saved a lot of time than traditional fuzzy cluster algorithm. The application result indicated: the new algorithm improved speed, reliability and accuracy of TCM tongue diagnosis, also met the requirements of intellectualization and digitization.
  • Keywords
    data mining; fuzzy set theory; medicine; patient diagnosis; pattern clustering; rough set theory; fuzzy rough set; grid clustering; rules mining; tongue diagnosis system; traditional Chinese medicine; Application software; Clustering algorithms; Deformable models; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Inference algorithms; Set theory; Tongue; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-2107-7
  • Electronic_ISBN
    978-1-4244-2108-4
  • Type

    conf

  • DOI
    10.1109/WiCom.2008.2994
  • Filename
    4681183