On generalized intuitionistic fuzzy rough approximation operators

被引:198
|
作者
Zhou, Lei [1 ,2 ]
Wu, Wei-Zhi [1 ]
机构
[1] Zhejiang Ocean Univ, Sch Math Phys & Informat Sci, Zhoushan 316004, Zhejiang, Peoples R China
[2] Xi An Jiao Tong Univ, Fac Sci, Inst Informat & Syst Sci, Xian 710049, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
approximation operators; fuzzy sets; intuitionistic fuzzy relations; intuitionistic fuzzy rough sets; intuitionistic fuzzy sets; rough sets;
D O I
10.1016/j.ins.2008.01.012
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In rough set theory, the lower and upper approximation operators defined by binary relations satisfy many interesting properties. Various generalizations of Pawlak's rough approximations have been made in the literature over the years. This paper proposes a general framework for the study of relation-based intuitionistic fuzzy rough approximation operators within which both constructive and axiomatic approaches are used. In the constructive approach, a pair of lower and upper intuitionistic fuzzy rough approximation operators induced from an arbitrary intuitionistic fuzzy relation are defined. Basic properties of the intuitionistic fuzzy rough approximation operators are then examined. By introducing cut sets of intuitionistic fuzzy sets, classical representations of intuitionistic fuzzy rough approximation operators are presented. The connections between special intuitionistic fuzzy relations and intuitionistic fuzzy rough approximation operators are further established. Finally, an operator-oriented characterization of intuitionistic fuzzy rough sets is proposed, that is, intuitionistic fuzzy rough approximation operators are defined by axioms. Different axiom sets of lower and upper intuitionistic fuzzy set-theoretic operators guarantee the existence of different types of intuitionistic fuzzy relations which produce the same operators. (c) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:2448 / 2465
页数:18
相关论文
共 50 条
  • [21] Generalized Aggregation Operators for Intuitionistic Fuzzy Sets
    Zhao, Hua
    Xu, Zeshui
    Ni, Mingfang
    Liu, Shousheng
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2010, 25 (01) : 1 - 30
  • [22] Rough Ideal Statistical Convergence via Generalized Difference Operators in Intuitionistic Fuzzy Normed Spaces
    Kaur, Manpreet
    Chawla, Meenakshi
    Antal, Reena
    COMMUNICATIONS IN MATHEMATICS AND APPLICATIONS, 2024, 15 (01): : 221 - 241
  • [23] Axiomatic Characterizations of Reflexive and T-Transitive I-Intuitionistic Fuzzy Rough Approximation Operators
    Wu, Wei-Zhi
    Xu, You-Hong
    Li, Tong-Jun
    Wang, Xia
    ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, RSFDGRC 2015, 2015, 9437 : 218 - 229
  • [24] Interval-Valued Intuitionistic Fuzzy Soft Rough Approximation Operators and Their Applications in Decision Making Problem
    Mukherjee A.
    Mukherjee A.
    Annals of Data Science, 2022, 9 (03): : 611 - 625
  • [25] Interval-Valued Intuitionistic Fuzzy Soft Rough Approximation Operators and Their Applications in Decision Making Problem
    Anjan Mukherjee
    Abhik Mukherjee
    Annals of Data Science, 2022, 9 : 611 - 625
  • [26] Rough approximation operators based on quantale-valued fuzzy generalized neighborhood systems
    Zhao, F. F.
    Li, L. Q.
    Sun, S. B.
    Jin, Q.
    IRANIAN JOURNAL OF FUZZY SYSTEMS, 2019, 16 (06): : 53 - 63
  • [27] Characteristic numbers and approximation operators in generalized rough approximation system
    Ma, Liwen
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2021, 139 (139) : 166 - 184
  • [28] Generalized intuitionistic fuzzy hybrid Choquet averaging operators
    Fanyong Meng
    Qiang Zhang
    Journal of Systems Science and Systems Engineering, 2013, 22 : 112 - 122
  • [29] On Modal Operators over the Generalized Intuitionistic Fuzzy Set
    Baloui Jamkhaneh, Ezzatallah
    Nadarajah, Saralees
    GAZI UNIVERSITY JOURNAL OF SCIENCE, 2018, 31 (01): : 222 - 234
  • [30] Generalized Point Operators for Aggregating Intuitionistic Fuzzy Information
    Xia, Meimei
    Xu, Zeshui
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2010, 25 (11) : 1061 - 1080