• DocumentCode
    2346134
  • Title

    An ANN-based clustering analysis algorithm with dynamic data window

  • Author

    Tianhao, Tang ; Tianzhen, Wang

  • Author_Institution
    Electr. & Control Eng. Inst., Shanghai Maritime Univ., China
  • Volume
    1
  • fYear
    2005
  • fDate
    26-29 June 2005
  • Firstpage
    581
  • Abstract
    Clustering analysis is an important approach of data mining. This paper presents an ANN-based clustering analysis algorithm with dynamic data window (DDW). Comparing with k-means algorithm merged in density-based and integrated clustering analysis algorithm, the new clustering analysis algorithm based on artificial neural networks and combining with DDW has more valuable in data mining. This algorithm can immensely avoid the effect on accumulation points from boundary points, and can automatically find representative accumulation points in all kings of shapes. Furthermore its applications in CIS will be discussed in the paper. Some analysis results show the significant improvement to ship-routing design with the clustering analysis algorithm based on ANN and DDW in database of CIS.
  • Keywords
    data mining; neural nets; pattern clustering; artificial neural networks; clustering analysis; data mining; dynamic data window; k-means algorithm; Algorithm design and analysis; Artificial neural networks; Clustering algorithms; Control engineering; Data mining; Geographic Information Systems; Heuristic algorithms; Partitioning algorithms; Shape; Visual databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation, 2005. ICCA '05. International Conference on
  • Print_ISBN
    0-7803-9137-3
  • Type

    conf

  • DOI
    10.1109/ICCA.2005.1528185
  • Filename
    1528185