Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the ranking values of fuzzy sets

被引：28
|
作者：
Lee, Li-Wei [1 ]
Chen, Shyi-Ming [1 ,2 ]
机构：
[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan
[2] Jinwen Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2008年 / 35卷 / 03期
关键词：
fuzzy interpolative reasoning; ranking values; ranking proportional interpolative coefficients; sparse fuzzy rule-based systems;
D O I：
10.1016/j.eswa.2007.07.027
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy interpolative reasoning is an important research topic of sparse fuzzy rule-based systems. In recent years, some methods have been presented for dealing with fuzzy interpolative reasoning. However, the involving fuzzy sets appearing in the antecedents of fuzzy rules of the existing fuzzy interpolative reasoning methods must be normal and non-overlapping. Moreover, the reasoning conclusions of the existing fuzzy interpolative reasoning methods sometimes become abnormal fuzzy sets. In this paper, in order to overcome the drawbacks of the existing fuzzy interpolative reasoning methods, we present a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the ranking values of fuzzy sets. The proposed fuzzy interpolative reasoning method can handle the situation of non-normal and overlapping fuzzy sets appearing in the antecedents of fuzzy rules. It can overcome the drawbacks of the existing fuzzy interpolative reasoning methods in sparse fuzzy rule-based systems. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：850 / 864
页数：15
相关论文
共 50 条
  • [1] Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the slopes of fuzzy sets
    Chen, Shyi-Ming
    Hsin, Wen-Chyuan
    Yang, Szu-Wei
    Chang, Yu-Chuan
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (15) : 11961 - 11969
  • [2] Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on piecewise fuzzy entropies of fuzzy sets
    Chen, Shyi-Ming
    Chen, Ze-Jin
    [J]. INFORMATION SCIENCES, 2016, 329 : 503 - 523
  • [3] Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems
    Chen, Shyi-Ming
    Chang, Yu-Chuan
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (08) : 9564 - 9572
  • [4] Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on interval type-2 fuzzy sets
    Chen, Shyi-Ming
    Lee, Li-Wei
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (08) : 9947 - 9957
  • [5] A New Method for Fuzzy Interpolative Reasoning in Sparse Fuzzy Rule-Based Systems
    Chang, Yu-Chuan
    Chen, Shyi-Ming
    [J]. 2012 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY2012), 2012, : 400 - 405
  • [6] A new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems
    Lee, Li-Wei
    Chen, Shyi-Ming
    [J]. NEW TRENDS IN APPLIED ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2007, 4570 : 745 - +
  • [7] Fuzzy Interpolative Reasoning for Sparse Fuzzy-Rule-Based Systems Based on the Areas of Fuzzy Sets
    Chang, Yu-Chuan
    Chen, Shyi-Ming
    Liau, Churn-Jung
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (05) : 1285 - 1301
  • [8] Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on transformation techniques
    Ko, Yuan-Kai
    Chen, Shyi-Ming
    Pan, Jeng-Shyang
    [J]. PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 3613 - +
  • [9] Fuzzy Interpolative Reasoning for Sparse Fuzzy Rule-Based Systems Based on α-Cuts and Transformations Techniques
    Chen, Shyi-Ming
    Ko, Yuan-Kai
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (06) : 1626 - 1648
  • [10] Fuzzy Rule-Based Interpolative Reasoning: A Survey
    Li, Fang-Yi
    Li, Ying
    Yang, Jing
    [J]. Jisuanji Xuebao/Chinese Journal of Computers, 2022, 45 (08): : 1687 - 1711
12345