Limitations of quantitative operator fuzzy logic

被引：4
|
作者：
Deng, AS [1 ]
Zhang, LY
机构：
[1] NE Normal Univ, Dept Comp Sci, Changchun 130024, Peoples R China
[2] Jilin Univ Technol, Sch Traff Engn, Changchun 130025, Peoples R China
来源：
SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES | 1998年 / 41卷 / 06期
基金：
中国国家自然科学基金;
关键词：
operator fuzzy logic; operator lattice; resolution;
D O I：
10.1007/BF02917044
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Quantitative models of operator fuzzy logic are discussed. It is proved that there is a unique real polynomial function that can be used to characterize the composition operation between fuzzy operators in a quantitative model of operator fuzzy logic. Based on this polynomial function, we redefine a new quantitative operator fuzzy logic NOFL by revising the existing suggested alternatives. It can be seen that it is hard for a quantitative model of operator fuzzy logic to be both theoretically sound and intuitively acceptable.
引用
收藏
页码：608 / 616
页数：9
相关论文
共 50 条
  • [31] Completeness of (a #956;,a #957;)-resolution principle of intuitionistic operator fuzzy logic
    Zheng, Hongliang
    Xu, Benqiang
    Zou, Li
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007), 2007,
  • [32] Quantitative methods in archaeological prediction: From binary to fuzzy logic
    Hatzinikolaou, EG
    [J]. GIS and Archaeological Site Location Modeling, 2006, : 437 - 446
  • [33] Fuzzy logic approach to the assessment of operator's safety during ship machinery
    Kowalewski, T.
    Podsiadlo, A.
    Tarelko, W.
    [J]. PROGRESS IN SAFETY SCIENCE AND TECHNOLOGY, VOL 6, PTS A AND B, 2006, 6 : 533 - 538
  • [34] Utilizing fuzzy logic controller in manufacturing facilities design: Machine and operator allocation
    Tashtoush, Tariq
    Alazzam, Azmi
    Rodan, Ali
    [J]. COGENT ENGINEERING, 2020, 7 (01):
  • [35] Research of the Operator's Advisory System Based on Fuzzy Logic for Pelletizing Equipment
    Andriukaitis, Darius
    Laucka, Andrius
    Valinevicius, Algimantas
    Zilys, Mindaugas
    Markevicius, Vytautas
    Navikas, Dangirutis
    Sotner, Roman
    Petrzela, Jiri
    Jerabek, Jan
    Herencsar, Norbert
    Klimenta, Dardan
    [J]. SYMMETRY-BASEL, 2019, 11 (11):
  • [36] LAMBDA-RESOLUTION AND INTERPRETATION OF LAMBDA-IMPLICATION IN FUZZY OPERATOR LOGIC
    LIU, XH
    FANG, KY
    TSAI, JP
    WEIGERT, T
    [J]. INFORMATION SCIENCES, 1991, 56 (1-3) : 259 - 278
  • [37] Mining of Quantitative Association Rule on Ozone Database Using Fuzzy Logic
    Rajeswari, A. M.
    Devi, M. S. Karthika
    Deisy, C.
    [J]. MATHEMATICAL MODELLING AND SCIENTIFIC COMPUTATION, 2012, 283 : 488 - 494
  • [38] A testbed for quantitative assessment of intrusion detection systems using fuzzy logic
    Singaraju, G
    Teo, L
    Zheng, YL
    [J]. SECOND IEEE INTERNATIONAL INFORMATION ASSURANCE WORKSHOP, PROCEEDINGS, 2004, : 79 - 93
  • [39] Decision Analysis Methods Combining Quantitative Logic and Fuzzy Soft Sets
    Zhang, Jialu
    Wu, Xia
    Lu, Ruhua
    [J]. INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2020, 22 (06) : 1801 - 1814
  • [40] Fuzzy adaptive logic networks as hybrid models of quantitative software engineering
    Pedrycz, W
    Breuer, A
    Pizzi, NJ
    [J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2006, 12 (02): : 189 - 209
12345