• DocumentCode
    2491017
  • Title

    A mountain means clustering algorithm

  • Author

    Wang, Junnian ; Liu, Jianxun ; Liu, Lanxia

  • Author_Institution
    Knowledge Grid Lab., Hunan Univ. of Sci. & Technol., Xiangtan
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    5045
  • Lastpage
    5049
  • Abstract
    A modified mountain clustering algorithm based on the hill valley function is proposed. Firstly, the grid and the mountain function are constructed in data space according to the mountain clustering method, and the mountain values of the data are computed. Secondly, the hill valley function is introduced to partition the data distributed on each peak. If the hill valley functionpsila value of two datum equal to 1, it means these two datum are on the same mountain and belong to thee same cluster, otherwise they are not. Finally, the means of data samples in each cluster are computed as the clustering centres. The testing of three data base indicate that the proposed mountain means clustering algorithm can categorise the clustering centres and the data numbers in each clusters exactly as well as efficiently.
  • Keywords
    data analysis; pattern clustering; clustering analysis; data samples; hill valley function; mountain clustering algorithm; Automation; Clustering algorithms; Clustering methods; Cognition; Grid computing; Intelligent control; Particle swarm optimization; Pattern analysis; Space technology; Testing; constructing grid; data cluster; hill valley function; mountain clustering method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593748
  • Filename
    4593748