Weighted fuzzy interpolative reasoning systems based on interval type-2 fuzzy sets

被引：24

作者：

Chen, Shyi-Ming ^{[1
]}

Lee, Li-Wei ^{[2
]}

Shen, Victor R. L. ^{[3
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[2] De Lin Inst Technol, Dept Comp & Commun Engn, New Taipei City, Taiwan

[3] Natl Taipei Univ, Dept Comp Sci & Informat Engn, New Taipei City, Taiwan

来源：

INFORMATION SCIENCES | 2013年 / 248卷

关键词：

Fuzzy interpolative reasoning; Interval type-2 fuzzy sets; Sparse fuzzy rule-based systems; Weighted fuzzy interpolative reasoning; RULE INTERPOLATION; LOGIC CONTROLLERS; OPTIMIZATION; RATIO;

D O I：

10.1016/j.ins.2013.05.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on interval type-2 fuzzy sets. We also apply the proposed weighted fuzzy interpolative reasoning method to deal with the truck backer-upper control problem. The proposed method satisfies the seven evaluation indices for fuzzy interpolative reasoning. The experimental results show that the proposed method outperforms the existing methods. It provides us with a useful way for dealing with fuzzy interpolative reasoning in sparse fuzzy rule-based systems. (C) 2013 Elsevier Inc. All rights reserved.

引用

页码：15 / 30

页数：16

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