• DocumentCode
    1872825
  • Title

    Recent trends in Ant Colony Optimization and data clustering: A brief survey

  • Author

    Chandrasekhar, Udaigiri ; Naga, P.R.P.

  • Author_Institution
    Sch. of Inf. Technol. & Eng., VIT Univ., Vellore, India
  • fYear
    2011
  • fDate
    7-9 Sept. 2011
  • Firstpage
    32
  • Lastpage
    36
  • Abstract
    Cluster Analysis is a popular data analysis and data mining technique. High quality and fast clustering algorithms play a vital role for users to navigate, effectively organize the data and summarize data. Ant Colony Optimization (ACO), a Swarm Intelligence technique, integrated with clustering algorithms, is being used by many applications for past few years. In this paper we discuss recent improvements on clustering algorithms like PP (Project Pursuit) based on the ACO algorithm for high dimensional data, recent applications of Data Clustering with ACO, application of Ant-based clustering algorithm for object finding by multiple robots in image processing field and the hybrid PSO/ACO algorithm for better optimized results.
  • Keywords
    data analysis; data mining; image processing; multi-robot systems; particle swarm optimisation; pattern clustering; ACO algorithm; PSO; ant colony optimization; ant-based clustering algorithm; cluster analysis; data analysis; data clustering; data mining technique; image processing field; multiple robots; project pursuit; swarm intelligence technique; Algorithm design and analysis; Ant colony optimization; Clustering algorithms; Particle swarm optimization; Partitioning algorithms; Robot kinematics; Ant Colony Optimization (ACO); Cluster Analysis; Particle Swarm Optimization (PSO); Swarm Intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Agent and Multi-Agent Systems (IAMA), 2011 2nd International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4577-0876-3
  • Type

    conf

  • DOI
    10.1109/IAMA.2011.6048999
  • Filename
    6048999