An Integrated Framework for Learning Fuzzy Cognitive Map using RCGA and NHL Algorithm

The methodology of developing fuzzy cognitive map (FCM) still exhibited weaknesses. This paper investigated a hybrid framework for learning FCM, which was combined of the real-coded genetic (RCGA) algorithm and nonlinear Hebbian learning (NHL) algorithm. This approach combined the synergistic theori...

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Bibliographic Details
Published in2008 4th International Conference on Wireless Communications, Networking and Mobile Computing pp. 1 - 5
Main Authors Zhu, Yanchun, Zhang, Wei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2008
Subjects
Collaboration
Data mining
Finance
Flowcharts
Fuzzy cognitive maps
Fuzzy logic
Genetic algorithms
Hebbian theory
Mathematical model
Neural networks
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Summary:The methodology of developing fuzzy cognitive map (FCM) still exhibited weaknesses. This paper investigated a hybrid framework for learning FCM, which was combined of the real-coded genetic (RCGA) algorithm and nonlinear Hebbian learning (NHL) algorithm. This approach combined the synergistic theories of neural networks and fuzzy logic. The hybrid algorithm is introduced, presented and applied successfully in real-world problems of partner selection.
ISBN:9781424421077
1424421071
ISSN:2161-9646
DOI:10.1109/WiCom.2008.2527