• DocumentCode
    2257990
  • Title

    Industrial Clusters Evolution Research Based on the SGA

  • Author

    Yajuan, Yang ; Pingan, Wang ; Wenxue, Niu

  • Author_Institution
    Financial & Trade Dept., Dongguan Univ. of Technol., Dongguan, China
  • fYear
    2010
  • fDate
    11-14 Dec. 2010
  • Firstpage
    117
  • Lastpage
    121
  • Abstract
    From the evolution view point, the evolving rules of industry clusterings are investigated by multi-agent system modeling method and the genetic algorithms is employed as the learning algorithm of an agent. Firstly, industrial clusterings is formed as a conceptual model which is a virtual multi-agent system, Secondly, the basic genetic algorithm is established for identifying an agent´s intelligent learning, Thirdly, simulation results are carried out based on Matlab2007b for the evolving of this multi-agent system, Finally, the research results feedbacks the industrial clusterings: analysis made for the evolution rules of the industry clusters being brought on the interactions of individual agent. The study in this paper shows that the evolution of industrial clusters comes from the complex interaction of agents so as to adapt the environment. Driver for the evolution of industrial clusters is the leading action of initiative enterprize. It is the case that the innovations of these enterprisers drives the whole industry going forward as well as the other members of industry clusterings.
  • Keywords
    commerce; genetic algorithms; learning (artificial intelligence); multi-agent systems; Matlab2007b; SGA; conceptual model; genetic algorithm; industrial clustering; industrial clusters evolution; industry clustering; intelligent learning; learning algorithm; multiagent system modeling; virtual multiagent system; Concept Models; Industrial Clustering; Multi-agent System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security (CIS), 2010 International Conference on
  • Conference_Location
    Nanning
  • Print_ISBN
    978-1-4244-9114-8
  • Electronic_ISBN
    978-0-7695-4297-3
  • Type

    conf

  • DOI
    10.1109/CIS.2010.33
  • Filename
    5696245