Approximation of fuzzy functions by regular fuzzy neural networks

被引：25
|
作者：
Huang, Huan [1 ]
Wu, Congxin [2 ]
机构：
[1] Jimei Univ, Dept Math, Xiamen 361021, Peoples R China
[2] Harbin Inst Technol, Dept Math, Harbin 150001, Peoples R China
来源：
FUZZY SETS AND SYSTEMS | 2011年 / 177卷 / 01期
关键词：
Regular fuzzy neural networks; Zadeh's extension principle; Approximation; Fuzzy functions; Fuzzy numbers; Supremum metric; Level convergence; LEVEL CONVERGENCE; ZADEHS EXTENSIONS; VALUED FUNCTIONS; CAPABILITIES;
D O I：
10.1016/j.fss.2011.04.013
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we investigate the ability of regular fuzzy neural networks to provide approximations to fuzzy functions. Since the operation of regular fuzzy neural networks is based on Zadeh's extension principle, we first present a level characterization of the Zadeh's extensions of level-continuous fuzzy-valued functions and consider the continuity of these extensions. On the basis of this, we give characterizations of fuzzy functions which can be approximated by a class of four-layer regular fuzzy neural networks according to supremum-metric and level convergence. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：60 / 79
页数：20
相关论文
共 50 条
  • [31] Regular Fuzzy Equivalences on Two - Mode Fuzzy Networks
    Jancic, Zorana
    Stankovic, Ivan
    Micic, Ivana
    FILOMAT, 2018, 32 (07) : 2677 - 2684
  • [32] STATISTICAL FUZZY APPROXIMATION TO FUZZY DIFFERENTIABLE FUNCTIONS BY FUZZY LINEAR OPERATORS
    Duman, Oktay
    HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, 2010, 39 (04): : 497 - 514
  • [33] Research on function approximation capabilities of fuzzy backpropagation neural networks
    Wang, S.-T.
    Zhu, X.-M.
    Huadong Chuanbo Gongye Xueyuan Xuebao/Journal of East China Shipbuilding Institute, 2001, 15 (04): : 44 - 48
  • [34] Fuzzy polynomial neural networks for approximation of the compressive strength of concrete
    Zarandi, M. H. Fazel
    Tuerksen, I. B.
    Sobhani, J.
    Ramezanianpour, A. A.
    APPLIED SOFT COMPUTING, 2008, 8 (01) : 488 - 498
  • [35] Dynamic fuzzy neural networks - A novel approach to function approximation
    Wu, SQ
    Er, MJ
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2000, 30 (02): : 358 - 364
  • [36] Approximation analysis of feedforward regular fuzzy neural network with two hidden layers
    Liu, PY
    Li, HX
    FUZZY SETS AND SYSTEMS, 2005, 150 (02) : 373 - 396
  • [37] Fuzzy neural networks
    Rao, DH
    IETE JOURNAL OF RESEARCH, 1998, 44 (4-5) : 227 - 236
  • [38] Type 2 fuzzy neural networks: An interpretation based on fuzzy inference neural networks with fuzzy parameters
    Rutkowska, D
    PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOL 1 & 2, 2002, : 1180 - 1185
  • [39] Fuzzy regression by fuzzy number neural networks
    Dunyak, JP
    Wunsch, D
    FUZZY SETS AND SYSTEMS, 2000, 112 (03) : 371 - 380
  • [40] Fuzzy polynomial regression with fuzzy neural networks
    Mosleh, M.
    Otadi, M.
    Abbasbandy, S.
    APPLIED MATHEMATICAL MODELLING, 2011, 35 (11) : 5400 - 5412
12345