Partitioning study of complex system

Authors:
He Yue;Lin Chun-Mei
Affiliations:
Department of Mathematics, Shaoxing College of Arts and Sciences, Shaoxing, Zhejiang, China;Department of Computer, Shaoxing College of Arts and Sciences, Shaoxing, Zhejiang, China
Venue:
WSEAS TRANSACTIONS on SYSTEMS
Year:
2008

Citing 13
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WSEAS TRANSACTIONS on SYSTEMS

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Abstract

Whether the design of knowledge base or the modeling of complex systems, when systems are characterized as complex systems with high dimension and a variety of variables and factors, to reduce complexity are necessary. Fuzzy cognitive maps (FCM) are a soft computing method for simulation and analysis of complex system, which combines the fuzzy logic with theories of neural networks. It is flexible in system design, model and control, the comprehensive ope ration and the abstractive representation of behavior for complex systems. When the complexity of the system, the application and maintenance of FCM become more difficult, in particular, the inference is difficult to achieve and not even gets the results. Therefore we present to partition the complex fuzzy cognitive map into smaller chunks based on genetic algorithm in this paper. We construct partitioning rules and criticize rules. Finally, an illustrative example is provided, and its results suggest that the method is capable of partitioning fuzzy cognitive map.