• DocumentCode
    2311257
  • Title

    A similarity-based clustering algorithm for fuzzy data

  • Author

    Hung, Wen-Liang ; Yang, Miin-Shen

  • Author_Institution
    Grad. Inst. of Comput. Sci., Nat. Hsinchu Univ. of Educ., Hsinchu, Taiwan
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper we propose a similarity-based clustering algorithm for handling LR-type fuzzy numbers. The proposed method does not need to specify a cluster number and initial values in which it is robust to initial values, cluster number, cluster shapes, noise and outliers for clustering LR-type fuzzy data. Numerical examples and real data demonstrate the effectiveness of the proposed clustering algorithm.
  • Keywords
    data analysis; fuzzy set theory; pattern clustering; statistical analysis; LR-type fuzzy numbers; cluster number; cluster shapes; fuzzy data; noise; similarity-based clustering algorithm; Clustering algorithms; Correlation; Couplings; Fuzzy sets; Physics; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-6919-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2010.5584601
  • Filename
    5584601
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2311257