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Algorithm and Simulation of Chinese Traditional Industrial Clusters Low Carbon Evolution Based on Evolutionary Games Theory on Complex Networks

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Abstract:

Industrial clusters are complex networks formed by numerous agents who continuously imitate, learn from each other and make optimal choice accordingly. The paper uses random learning game and multi-agent system models to construct a Chinese traditional industrial clusters low carbon evolution model and introduce an algorithm based on the network external effect and characteristics of agents adaptive behavior. Then the simulation of low-carbon competition, emergence and evolution was conducted, which produced some valuable conclusions.

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Info:

Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

2047-2052

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.734-737.2047

Citation:

Cite this paper

Online since:

August 2013

Authors:

Ru Guo Fan*, Hong Juan Zhang, Peng Fei Zhang

Keywords:

Complex Network, Evolutionary Game Theory, Industrial Cluster, Low-Carbon Evolution

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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