Refinement CTIN for General Type-2 Fuzzy Logic Systems

被引：0
|
作者：
Long Thanh Ngo [1 ]
机构：
[1] Le Quy Don Tech Univ, Fac Informat Technol, Dept Informat Syst, Hanoi, Vietnam
来源：
IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011) | 2011年
关键词：
Type-2 Fuzzy Sets; Type-2 Fuzzy Logic Systems; Type-2 Fuzzy Inference; Geometric Representation; ALPHA-PLANE REPRESENTATION; SETS THEORY; DEFUZZIFICATION;
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：
Triangulated irregular network (TIN) has been used for representing general type-2 fuzzy sets and gained some results of reducing computational complexity. In general, TIN-based algorithms are still complex and difficulty to deploy in applications. So, an approach based on refinement constraint TIN (CTIN) for representing general type-2 fuzzy set is proposed. The paper deals with the use CTIN in general type-2 fuzzy logic systems (GT2FLS). Operations are developed for general type-2 fuzzy sets. A T2FLS is designed and implemented in comparing previous approaches under an application of robot navigation.
引用
收藏
页码：1225 / 1232
页数：8
相关论文
共 50 条
  • [21] Type-2 fuzzy logic systems: Type-reduction
    Karnik, NN
    Mendel, JM
    1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 2046 - 2051
  • [22] A Simple Matlab Simulink Model for Adaptive General Type-2 Fuzzy Logic Systems
    Mohammadzadeh, Ardashir
    Ghavifekr, Amir Aminzadeh
    2021 7TH INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION AND AUTOMATION (ICCIA), 2021, : 317 - 320
  • [23] Automatic Learning of General Type-2 Fuzzy Logic Systems using Simulated Annealing
    Almaraashi, Majid
    John, Robert
    Hopgood, Adrian
    2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2014, : 2384 - 2390
  • [24] Forecasting by TSK general type-2 fuzzy logic systems optimized with genetic algorithms
    Chen, Yang
    Wang, Dazhi
    Ning, Wu
    OPTIMAL CONTROL APPLICATIONS & METHODS, 2018, 39 (01): : 393 - 409
  • [25] On the Monotonicity of Interval Type-2 Fuzzy Logic Systems
    Li, Chengdong
    Yi, Jianqiang
    Zhang, Guiqing
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (05) : 1197 - 1212
  • [26] Toolbox for Interval Type-2 Fuzzy Logic Systems
    Zamani, Mohsen
    Nejati, Hossein
    Jahromi, Amin T.
    Partovi, Ali Reza
    Nobari, Sadegh H.
    Shirazi, Ghasem N.
    PROCEEDINGS OF THE 11TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2008,
  • [27] Simplified Interval Type-2 Fuzzy Logic Systems
    Mendel, Jerry M.
    Liu, Xinwang
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (06) : 1056 - 1069
  • [28] Efficient triangular type-2 fuzzy logic systems
    Starczewski, Janusz T.
    International Journal of Approximate Reasoning, 2009, 50 (05): : 799 - 811
  • [29] Research on Type-2 TSK Fuzzy Logic Systems
    Zheng, Gao
    Wang, Jing
    Jiang, Lin
    FUZZY INFORMATION AND ENGINEERING, VOLUME 2, 2009, 62 : 491 - +
  • [30] Efficient triangular type-2 fuzzy logic systems
    Starczewski, Janusz T.
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2009, 50 (05) : 799 - 811
12345