Uncertainty and reduction of variable precision multigranulation fuzzy rough sets based on three-way decisions

被引:55
作者
Feng, Tao [1 ]
Fan, Hui-Tao [1 ]
Mi, Ju-Sheng [2 ]
机构
[1] Hebei Univ Sci & Technol, Sch Sci, Shijiazhuang 050018, Peoples R China
[2] Hebei Normal Univ, Coll Math & Informat Sci, Shijiazhuang 050024, Peoples R China
基金
中国国家自然科学基金;
关键词
Variable precision multigranulation fuzzy rough sets; Rough membership degree; Uncertainty; Reduction; ATTRIBUTE REDUCTION; GRANULATION; ENTROPY; APPROXIMATION; PARTITION;
D O I
10.1016/j.ijar.2017.03.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper studies reduction of a multigranulation fuzzy information system by using uncertainty measures based on variable precision multigranulation decision-theoretic fuzzy rough sets, avoiding the positive region and negative region changing to small ones. Firstly we review variable precision multigranulation fuzzy rough sets and the decision method based on three-way decisions. Then, a double parameter rough membership degree of a fuzzy set is constructed based on variable precision multigranulation decision-theoretic fuzzy rough sets. A double parameter uncertainty measure of a multigranulation decision system is also proposed. In order to keep the decision-makings of certain elements, which are in the positive region or negative region, unchanged, we use the double parameter uncertainty measure of a multigranulation decision system to reduce the consistent decision system. Finally, we propose a conditional uncertainty measure and discuss the decision-theoretic reduction of granulation set and conditional attribute set in inconsistent views. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:36 / 58
页数:23
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