Error calculation of the HOSVD-based rule base reduction in hierarchical fuzzy systems

被引:4
|
作者
Toth-Laufer, Edit [1 ]
Rovid, Andras [2 ]
Takacs, Marta [2 ,3 ]
机构
[1] Obuda Univ, Donat Banki Fac Mech & Safety Engn, Nepszinhaz Str 8, H-1081 Budapest, Hungary
[2] Obuda Univ, John von Neumann Fac Informat, Becsi Way 96-B, H-1034 Budapest, Hungary
[3] Univ Novi Sad, Teacher Training Fac, Strossmajer 12, Subotica, Serbia
基金
匈牙利科学研究基金会;
关键词
Fuzzy inference systems; HOSVD; Rule base reduction; Error calculation; Reduction optimization; TP MODEL TRANSFORMATION; TELEMEDICINE; OPTIMIZATION;
D O I
10.1016/j.fss.2015.12.018
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In real time evaluation systems the decision should be made in time to avoid the serious consequences. In the literature there are several techniques which aim to reduce the computational complexity of these kinds of systems. Among others the Higher Order Singular Value Decomposition (HOSVD) based reduction method is a useful tool for handling this problem. In the case when only non-exact reduction can be performed, the error calculation is also essential, because the reduction degree is based on the calculated error in these systems. In this paper the authors present the HOSVD reduction error calculation in hierarchical fuzzy systems using Mamdani-type inference and define a general formula which includes the propagated error from the previous levels of the hierarchy; in which the error bound, calculated by different ways, can be used and takes into account the case when not all the inputs contain a propagated error but only a few of them. Furthermore a greedy algorithm is presented for reduction optimization. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:67 / 82
页数:16
相关论文
共 50 条
  • [1] Similarity in hierarchical fuzzy rule - base systems
    Muresan, L
    László, KT
    Hirota, K
    PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOL 1 & 2, 2002, : 746 - 750
  • [2] Adaptation of TS fuzzy models without complexity expansion:: HOSVD-based approach
    Baranyi, P
    Várkonyi-Kóczy, AR
    Yam, Y
    Patton, RJ
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2005, 54 (01) : 52 - 60
  • [3] HOSVD-based Limited Feedback and Precoding Design for Massive MIMO Systems
    Zhu, Yu
    Tian, Yafei
    Yang, Chenyang
    2016 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC WORKSHOPS), 2016,
  • [4] Anytime Sport Activity Risk Level Calculation using HOSVD based Hierarchical Fuzzy Models
    Toth-Laufer, Edit
    Varkonyi-Koczy, Annamaria R.
    2013 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS PROCEEDINGS (MEMEA), 2013, : 300 - 305
  • [5] Adaption without rule base size expansion:: HOSVD based approach
    Baranyi, P
    Várkonyi-Kóczy, AR
    Yam, Y
    Michelberger, P
    IMTC 2002: PROCEEDINGS OF THE 19TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 & 2, 2002, : 221 - 226
  • [6] Fuzzy inversion and rule base reduction
    Baranyi, P
    Korondi, P
    Hashimoto, H
    Wada, M
    INES'97 : 1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS, PROCEEDINGS, 1997, : 301 - 306
  • [7] Simulation of a fuzzy controller for a tunnel bread oven with hierarchical rule-base reduction
    Cuahutle, DH
    Garcia, CAR
    COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION - EVOLUTIONARY COMPUTATION & FUZZY LOGIC FOR INTELLIGENT CONTROL, KNOWLEDGE ACQUISITION & INFORMATION RETRIEVAL, 1999, 55 : 230 - 235
  • [8] Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection
    Fernandez, A.
    del Jesus, M. J.
    Herrera, F.
    2010 FOURTH INTERNATIONAL WORKSHOP ON GENETIC AND EVOLUTIONARY FUZZY SYSTEMS (GEFS 2010), 2010, : 69 - 74
  • [9] Rule generation for hierarchical fuzzy systems
    Holve, R
    1997 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 1997, : 444 - 449
  • [10] Formation of hierarchical fuzzy rule systems
    Gabriel, TR
    Berthold, MR
    NAFIPS'2003: 22ND INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS PROCEEDINGS, 2003, : 87 - 92