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
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;
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
DOI :
10.1109/CIS.2010.33
