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http://dx.doi.org/10.5762/KAIS.2013.14.1.378

Design of Fuzzy Neural Networks Based on Fuzzy Clustering and Its Application  

Park, Keon-Jun (Department of Information Communication Engineering, Wonkwang University)
Lee, Dong-Yoon (Department of Electrical Electronic Engineering, Joongbu University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.14, no.1, 2013 , pp. 378-384 More about this Journal
Abstract
In this paper, we propose the fuzzy neural networks based on fuzzy c-means clustering algorithm. Typically, the generation of fuzzy rules have the problem that the number of fuzzy rules exponentially increases when the dimension increases. To solve this problem, the fuzzy rules of the proposed networks are generated by partitioning the input space in the scatter form using FCM clustering algorithm. The premise parameters of the fuzzy rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the learning of fuzzy neural networks is realized by adjusting connections of the neurons, and it follows a back-propagation algorithm. The proposed networks are evaluated through the application to nonlinear process.
Keywords
Fuzzy Clustering Algorithm; Fuzzy Neural Networks (FNNs); Nonlinear Process; Rule Generation; Scatter Partition of Input Space;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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