• DocumentCode
    3311728
  • Title

    Data clustering method based on ant swarm intelligence

  • Author

    Wang Yong ; Wei Peng-Cheng

  • Author_Institution
    Comput. Dept., Chongqing Educ. Coll., Chongqing, China
  • fYear
    2009
  • fDate
    8-11 Aug. 2009
  • Firstpage
    358
  • Lastpage
    361
  • Abstract
    Clustering analysis based on ant swarm intelligence is discussed. As traditional clustering algorithm is easy to obtain local optimum, it uses ant swarm intelligence to obtain global search. It improves the clustering by locating the objects in a cluster with the probability, which is updated by the pheromone, while the rule of updating pheromone is according to total within cluster variance. According to the simulation results, the proposed algorithm outperforms several existing approaches such as GA, SOM.
  • Keywords
    data mining; optimisation; pattern clustering; probability; search problems; ant swarm intelligence; data clustering analysis; data mining; global search; pheromone updation; probability; Ant colony optimization; Cities and towns; Clustering algorithms; Clustering methods; Computer science education; Data mining; Educational institutions; Particle swarm optimization; TV; Traveling salesman problems; aco; clustering; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4519-6
  • Electronic_ISBN
    978-1-4244-4520-2
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2009.5234558
  • Filename
    5234558