On answering the question "Where do I start in order to solve a new problem involving interval type-2 fuzzy sets?"

被引:64
|
作者
Mendel, Jerry M. [1 ]
机构
[1] Univ So Calif, Inst Signal & Image Proc, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90089 USA
关键词
Interval type-2 fuzzy sets; Representation Theorem; Embedded sets; Centroid; Uncertainty measures; Similarity; Fuzzy logic system; Linguistic weighted average; Fuzzistics; WEIGHTED AVERAGE; UNCERTAINTY; FUZZISTICS; REPRESENTATION; MODELS; WORDS;
D O I
10.1016/j.ins.2009.05.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper, which is tutorial in nature, demonstrates how the Embedded Sets Representation Theorem (RT) for a general type-2 fuzzy set (T2 FS), when specialized to an interval (I)T-2 FS, can be used as the starting point to solve many diverse problems that involve IT2 FSs. The problems considered are: set theoretic operations, centroid, uncertainty measures, similarity, inference engine computations for Mamdani IT2 fuzzy logic systems, linguistic weighted average, person membership function approach to type-2 fuzzistics, and Interval Approach to type-2 fuzzistics. Each solution obtained from the RT is a structural solution but is not a practical computational solution, however, the latter are always found from the former. It is this author's recommendation that one should use the RT as a starting point whenever solving a new problem involving IT2 FSs because it has had such great success in solving so many such problems in the past, and it answers the question "Where do I start in order to solve a new problem involving IT2 FSs?" (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:3418 / 3431
页数:14
相关论文
共 50 条
  • [21] Interval Type-2 Fuzzy Sets in Supplier Selection
    Tuerk, Seda
    John, Robert
    Oezcan, Ender
    [J]. 2014 14TH UK WORKSHOP ON COMPUTATIONAL INTELLIGENCE (UKCI), 2014, : 127 - 133
  • [22] The Reduction of Interval Type-2 LR Fuzzy Sets
    Chen, Chao-Lieh
    Chen, Shen-Chien
    Kuo, Yau-Hwang
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (04) : 840 - 858
  • [23] On Computing Normalized Interval Type-2 Fuzzy Sets
    Mendel, Jerry M.
    Rajati, Mohammad Reza
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (05) : 1335 - 1340
  • [24] Uncertainty measures for interval type-2 fuzzy sets
    Wu, Dongrui
    Mendel, Jerry M.
    [J]. INFORMATION SCIENCES, 2007, 177 (23) : 5378 - 5393
  • [25] Interval type-2 fuzzy sets in psychological interventions
    Wu, Zhanlin
    Mo, Hong
    Zhou, Min
    Tan, Dan
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES), 2013, : 238 - 242
  • [26] Multilevel AHP approach with interval type-2 fuzzy sets to portfolio selection problem
    Meniz, Busra
    Bas, Sema Akin
    Ozkok, Beyza Ahlatcioglu
    Tiryaki, Fatma
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 40 (05) : 8819 - 8829
  • [27] A New Extended TOPSIS Method Based on Interval Type-2 Fuzzy Sets
    Wang, Huidong
    Pan, Xiaohong
    He, Shifan
    Yao, Jinli
    Zhang, Xiaoyun
    [J]. PROCEEDINGS 2018 33RD YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2018, : 499 - 504
  • [28] Spectral Learning with Type-2 Fuzzy Numbers for Question/Answering System
    Celikyilmaz, Asli
    Turksen, I. Burhan
    [J]. PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE, 2009, : 1388 - 1393
  • [29] Fuzzy Feature Selection Based On Interval Type-2 Fuzzy Sets
    Cherif, Sahar
    Baklouti, Nesrine
    Alimi, Adel
    Snasel, Vaclav
    [J]. NINTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2016), 2017, 10341
  • [30] Fuzzy interpolative reasoning using interval type-2 fuzzy sets
    Lee, Li-Wei
    Chen, Shyi-Ming
    [J]. NEW FRONTIERS IN APPLIED ARTIFICIAL INTELLIGENCE, 2008, 5027 : 92 - 101