文章基本信息

标题：Design of Fuzzy Respective Space-Based Neuro-Fuzzy Networks for Pattern Recognition
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作者：Keon-Jun Park ; Yong-Kab Kim
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2013
卷号：7
期号：4
出版社：SERSC
摘要：In this paper, we introduce the design of fuzzy respective space-based neuro-fuzzy networks for pattern recognition. The proposed networks are realized by partitioning of the fuzzy respective input space to generate the fuzzy rules. The respectively partitioned spaces using fuzzy respective input space express the rules of the networks. The consequence part of the rules is represented by polynomial functions. The coefficients of consequence part of the rules are learned by the back-propagation algorithm. And we also optimize the proposed networks using real-coded genetic algorithms. A numerical example is given to evaluate the validity of the proposed networks for pattern recognition. As a result, this paper shows that the proposed networks have the good result together with fewer rules
关键词：Neuro-Fuzzy Networks (NFNs); Grid Partition; Fuzzy Respective Input Space; ;Genetic Algorithms (GAs); Pattern Recognition