A New Fuzzy Interpolative Reasoning Method Based on the Ratio of Fuzziness of Rough-Fuzzy Sets

被引：0
|
作者：
Chen, Shyi-Ming [1 ]
Cheng, Shou-Hsiung [2 ,3 ]
Chen, Ze-Jin [1 ]
机构：
[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan
[2] Chien Kuo Technol Univ, Dept Informat Management, Changhua, Taiwan
[3] Chien Kuo Technol Univ, Dept Kinesiol Hlth Leisure Studies, Changhua, Taiwan
来源：
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT I | 2015年 / 9011卷
关键词：
Degrees of fuzziness; Fuzzy interpolative reasoning; Rough-fuzzy sets; Ratio of fuzziness;
D O I：
10.1007/978-3-319-15702-3_53
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the ratio of fuzziness of polygonal rough-fuzzy sets, where the values of the antecedent variables and the consequence variables in the fuzzy rules are represented by polygonal rough-fuzzy sets. The experimental results show that the proposed fuzzy interpolative reasoning method outperforms the existing method for fuzzy interpolative reasoning in sparse fuzzy rule-based systems.
引用
收藏
页码：551 / 561
页数：11
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