Novel fuzzy ?-covering rough set models and their applications

被引：44
作者：
Dai, Jianhua [1 ,2 ]
Zou, Xiongtao [1 ,2 ]
Wu, Wei-Zhi [3 ]
机构：
[1] Hunan Normal Univ, Hunan Prov Key Lab Intelligent Comp & Language Inf, Changsha 410081, Peoples R China
[2] Hunan Normal Univ, Coll Informat Sci & Engn, Changsha 410081, Peoples R China
[3] Zhejiang Ocean Univ, Sch Informat Engn, Zhoushan 316022, Zhejiang, Peoples R China
来源：
INFORMATION SCIENCES | 2022年 / 608卷
基金：
中国国家自然科学基金;
关键词：
Fuzzy rough sets; Fuzzy ?-covering relation; Fuzzy ?-neighborhoods; Uncertainty measure; Attribute reduction; NEIGHBORHOOD OPERATORS; REDUCTION; MATRIX;
D O I：
10.1016/j.ins.2022.06.060
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 recent years, fuzzy fl-covering, as a natural extension of fuzzy coverings, has attracted considerable attention. However, existing fuzzy fl-neighborhood operators cannot accu-rately describe the relationship between objects, which greatly restricts the application of fuzzy fl-covering. For this reason, we first construct four new fuzzy fl-neighborhood operators by using the existing fuzzy fl-neighborhood operator and generalized fuzzy logic operators, and investigate their properties. To better portray the similarity between sam-ples, inspired by the definition of fuzzy similarity relation, we define the concept of fuzzy fl-covering relation. On this basis, we develop a new framework of fuzzy fl-covering rough set models. We further propose an attribute reduction method by employing the new fuzzy fl-covering relation, and design a heuristic attribute reduction algorithm with reference to an uncertainty measure called attribute significance. Finally, experimental results show the superiority of our proposed method through a series of experimental analyses.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码：286 / 312
页数：27
相关论文
共 48 条
[21]  
Li J.Y., 2002, KENT RIDGE BIOMEDICA
[22]   Generalized fuzzy rough approximation operators based on fuzzy coverings [J].
Li, Tong-Jun ;
Leung, Yee ;
Zhang, Wen-Xiu .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2008, 48 (03) :836-856
[23]   Information structures in a covering information system [J].
Li, Zhaowen ;
Huang, Dan ;
Liu, Xiaofeng ;
Xie, Ningxin ;
Zhang, Gangqiang .
INFORMATION SCIENCES, 2020, 507 :449-471
[24]   Deep learning for missing value imputation of continuous data and the effect of data discretization [J].
Lin, Wei-Chao ;
Tsai, Chih-Fong ;
Zhong, Jia Rong .
KNOWLEDGE-BASED SYSTEMS, 2022, 239
[25]   Novel matrix-based approaches to computing minimal and maximal descriptions in covering-based rough sets [J].
Liu, Caihui ;
Cai, Kecan ;
Miao, Duoqian ;
Qian, Jin .
INFORMATION SCIENCES, 2020, 539 :312-326
[26]  
Ma LW, 2016, FUZZY SET SYST, V294, P1, DOI [10.1016/j.fss.2015.05.0020165, 10.1016/j.fss.2015.05.002]
[27]   Topological and lattice structures of L-fuzzy rough sets determined by lower and upper sets [J].
Ma, Zhen Ming ;
Hui, Bao Qing .
INFORMATION SCIENCES, 2013, 218 :194-204
[28]   ROUGH SETS [J].
PAWLAK, Z .
INTERNATIONAL JOURNAL OF COMPUTER & INFORMATION SCIENCES, 1982, 11 (05) :341-356
[29]   A comparative study of fuzzy rough sets [J].
Radzikowska, Anna Maria ;
Kerre, Etienne E. .
FUZZY SETS AND SYSTEMS, 2002, 126 (02) :137-155
[30]   Variable precision diversified attribute multigranulation fuzzy rough set-based multi-attribute group decision making problems [J].
Sun, Bingzhen ;
Qi, Chang ;
Ma, Weimin ;
Wang, Ting ;
Zhang, Liye ;
Jiang, Chao .
COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 142
12345