• DocumentCode
    2967940
  • Title

    Shaping Up Clusters with PSO

  • Author

    Breaban, Mihaela ; Luchian, Silvia

  • Author_Institution
    Fac. of Comput. Sci., Alexandru loan Cuza Univ., Iasi, Romania
  • fYear
    2008
  • fDate
    26-29 Sept. 2008
  • Firstpage
    532
  • Lastpage
    537
  • Abstract
    This paper presents a method for enhancing the performance of current clustering algorithms; the method is based on Particle Swarm Optimization techniques. Namely, a preprocessing step aims at bringing rdquocloserrdquo objects which are likely to belong to the same cluster, while increasing the distance between objects likely to belong to different clusters. Experimental results show significantly improved performance for further clustering procedures especially when non-spherical clusters are involved.
  • Keywords
    particle swarm optimisation; pattern clustering; current clustering algorithm; particle swarm optimization; Algorithm design and analysis; Clustering algorithms; Clustering methods; Computer science; Euclidean distance; Particle swarm optimization; Partitioning algorithms; Scientific computing; Shape measurement; Size measurement; PSO; clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numeric Algorithms for Scientific Computing, 2008. SYNASC '08. 10th International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-0-7695-3523-4
  • Type

    conf

  • DOI
    10.1109/SYNASC.2008.70
  • Filename
    5204866