Interval Type-2 TSK+ Fuzzy Inference System

被引:0
|
作者
Li, Jie [1 ]
Yang, Longzhi [1 ]
Fu, Xin [2 ]
Chao, Fei [3 ]
Qu, Yanpeng [4 ]
机构
[1] Northumbria Univ, Dept Comp & Informat Sci, Fac Engn & Environm, Newcastle Upon Tyne NE1 8XT, Tyne & Wear, England
[2] Xiamen Univ, Sch Management, Xiamen, Peoples R China
[3] Xiamen Univ, Dept Cognit Sci, Xiamen, Peoples R China
[4] Dalian Maritime Univ, Informat Sci & Technol Coll, Dalian, Peoples R China
来源
2018 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | 2018年
基金
中国国家自然科学基金;
关键词
Interval type-2 TSK+; TSK fuzzy inference system; sparse rule base; imbalanced data set; fuzzy interpolation; INTERPOLATION; LOGIC; SETS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Type-2 fuzzy sets and systems can better handle uncertainties compared to its type-1 counterpart, and the widely applied Mamdani and TSK fuzzy inference approaches have been both extended to support interval type-2 fuzzy sets. Fuzzy interpolation enhances the conventional Mamdani and TKS fuzzy inference systems, which not only enables inferences when inputs are not covered by an incomplete or sparse rule base but also helps in system simplification for very complex problems. This paper extends the recently proposed fuzzy interpolation approach TSK+ to allow the utilization of interval type-2 TSK fuzzy rule bases. One illustrative case based on an example problem from the literature demonstrates the working of the proposed system, and the application on the cart centering problem reveals the power of the proposed system. The experimental investigation confirmed that the proposed approach is able to perform fuzzy inferences using either dense or sparse interval type-2 TSK rule bases with promising results generated.
引用
收藏
页数:8
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