Interpolation Functions Of General Type-2 Fuzzy Systems

被引:0
|
作者
Zhao, Shan [1 ]
Shi, Kaibo [1 ]
机构
[1] Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu 610106, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Type-2 fuzzy set; General type-2 fuzzy system; Interpolation function; Universal approximator; CENTROID-FLOW ALGORITHM; INTERVAL TYPE-2; LOGIC SYSTEMS; REDUCTION; SETS; CONTROLLER;
D O I
10.1007/s40815-024-01872-3
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 focuses on simplifying the use procedure and calculation of general type-2 fuzzy systems by way of extracting their the interpolation functions. Firstly, four kinds of fuzzification methods with special laws are designed to construct the general type-2 fuzzy sets in the antecedents and consequents of type-2 inference rules. On this basis, together with the KM algorithm, alpha\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}-plane representation and interpolation conclusions of interval type-2 fuzzy systems, three types of interpolation functions of general type-2 fuzzy systems are obtained. In the meantime, all of the interpolation functions have been proved as universal approximators. It can be seen that in future applications of general type-2 fuzzy systems, interpolation functions can be applied directly instead of conventional blocks. Because of the ingenious design of the general type-2 fuzzy sets on operations, the computation of general type-2 fuzzy systems has been greatly reduced. In order to verify the validity and superiority of the proposed methods, simulation results with a type-1 fuzzy system, an interval type-2 fuzzy system and two general type-2 fuzzy systems for the approximation problem of dynamic systems are presented. The simulations exhibit that the suggested approaches have good and desired performance.
引用
收藏
页数:17
相关论文
共 50 条
  • [41] Juzzy - A Java']Java based Toolkit for Type-2 Fuzzy Logic An object-oriented toolkit for the development of type-1, interval type-2 and general type-2 fuzzy systems
    Wagner, Christian
    PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON ADVANCES IN TYPE-2 FUZZY LOGIC SYSTEMS (T2FUZZ), 2013, : 45 - 52
  • [42] Systems identification using type-2 fuzzy neural network (Type-2 FNN) systems
    Lee, CH
    Lin, YC
    Lai, WY
    2003 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION, VOLS I-III, PROCEEDINGS, 2003, : 1264 - 1269
  • [43] Some General Comments on Fuzzy Sets of Type-2
    Walker, Carol L.
    Walker, Elbert A.
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2009, 24 (01) : 62 - 75
  • [44] A general type-2 fuzzy model for computing with words
    Jiang, Yuncheng
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2018, 33 (04) : 713 - 758
  • [45] Uncertainty measures for general Type-2 fuzzy sets
    Zhai, Daoyuan
    Mendel, Jerry M.
    INFORMATION SCIENCES, 2011, 181 (03) : 503 - 518
  • [46] Towards Interpretable General Type-2 Fuzzy Classifiers
    Lucas, Luis A.
    Centeno, Tania M.
    Delgado, Myriam R.
    2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, 2009, : 584 - 589
  • [47] Uncertainty Measures for General Type-2 Fuzzy Sets
    Zhai, Daoyuan
    Mendel, Jerry M.
    2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, 2009, : 281 - 286
  • [48] Introduction to type-2 fuzzy logic systems
    Karnik, NN
    Mendel, JM
    1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS, VOL 1-2, 1998, : 915 - 920
  • [49] Uncertainty in Interval Type-2 Fuzzy Systems
    Aminifar, Sadegh
    Marzuki, Arjuna
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
  • [50] Shadowed Type-2 Fuzzy Logic Systems
    Wijayasekara, Dumidu
    Linda, Ondrej
    Manic, Milos
    PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON ADVANCES IN TYPE-2 FUZZY LOGIC SYSTEMS (T2FUZZ), 2013, : 15 - 22