• DocumentCode
    2042375
  • Title

    Data clustering algorithms based on Swarm Intelligence

  • Author

    Bharne, Pankaj K. ; Gulhane, V.S. ; Yewale, Shweta K.

  • Author_Institution
    Sipna Coll. of Eng. & Tech., Amravati, India
  • Volume
    4
  • fYear
    2011
  • fDate
    8-10 April 2011
  • Firstpage
    407
  • Lastpage
    411
  • Abstract
    For a decade swarm Intelligence, an artificial intelligence discipline, is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). This paper also gives a comparative analysis of PSO and ACO for data clustering.
  • Keywords
    artificial intelligence; multi-agent systems; particle swarm optimisation; pattern clustering; ACO; PSO; ant colony optimization; artificial intelligence; data clustering algorithm; intelligent multiagent system; particle swarm optimization; social insect; swarm intelligence; Algorithm design and analysis; Ant colony optimization; Clustering algorithms; Genetic algorithms; Optimization; Particle swarm optimization; Signal processing algorithms; Comparison of Data Clustering Algorithms; Data Clustering; Data Clustering Algorithms Based on swarm Intelligence; Swarm Intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics Computer Technology (ICECT), 2011 3rd International Conference on
  • Conference_Location
    Kanyakumari
  • Print_ISBN
    978-1-4244-8678-6
  • Electronic_ISBN
    978-1-4244-8679-3
  • Type

    conf

  • DOI
    10.1109/ICECTECH.2011.5941931
  • Filename
    5941931