文章基本信息

标题：Successive Optimization of Interval Type-2 Fuzzy C-Means Clustering Algorithm-based Fuzzy Inference Systems
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作者：Keon-Jun Park ; Dong-Yoon Lee
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：design methodology of interval type-2 fuzzy c-means clustering algorithm-based fuzzy inference systems (IT2FCMFIS) is introduced in this paper. An interval type-2 fuzzy c-means (IT2FCM) clustering algorithm is developed to generate the fuzzy rules in the form of the scatter partition of input space. And the individual partitioned spaces describe the fuzzy rules equal to the number of clusters. The consequence part of the rule is represented by polynomial functions with interval set. To optimally construct of fuzzy model we exploit real-coded genetic algorithms with successive optimization. The proposed model is evaluated through the numeric experimentation
关键词：Fuzzy Inference Systems; Interval Type-2 Fuzzy C-Means Clustering; Scatter Partition; ;Genetic Algorithms; Successive Optimization