文章基本信息

标题：Nonlinear Characteristics of Fuzzy Scatter Partition-Based Fuzzy Inference System
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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：5
页码：77-86
出版社：SERSC
摘要：This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.
关键词：Fuzzy Scatter Partition; Fuzzy Inference Systems; Fuzzy C-Means Clustering Algorithm; Rule Generation; Nonlinear Process