• DocumentCode
    2436865
  • Title

    A Novel Clustering Algorithm with Ant Colony Optimization

  • Author

    Fu, Hui

  • Author_Institution
    Dept. of Comput. Sci., Guangdong Polytech. Normal Univ., Guangzhou
  • Volume
    2
  • fYear
    2008
  • fDate
    19-20 Dec. 2008
  • Firstpage
    66
  • Lastpage
    69
  • Abstract
    Clustering analysis is an important area of data mining. A kind of new clustering algorithm with ant colony optimization based on cluster center initialization is proposed in this paper. The new algorithm gives initialized cluster centers by different methods, then solves clustering problems by iterated method. Three methods of cluster center initialization are used in clustering algorithm with ant colony optimization - Sacc.Three datasets - butterfly data, iris and wine are chosen for the compare of three algorithms. The results of several times experiments show that the new algorithm is less in running time, is better in clustering effect and more stable than Sacc. Experimental results validate new algorithm´s efficiency.
  • Keywords
    data mining; iterative methods; optimisation; pattern clustering; ant colony optimization; cluster center initialization; clustering algorithm; clustering analysis; data mining; iterated method; Ant colony optimization; Application software; Clustering algorithms; Computational intelligence; Computer industry; Computer science; Conferences; Mining industry; Partitioning algorithms; Pattern analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3490-9
  • Type

    conf

  • DOI
    10.1109/PACIIA.2008.75
  • Filename
    4756736