Attribute Reduction Based on Related Families of Fuzzy covering rough sets

被引：0
|
作者：
Yang, Tian [1 ]
Li, Teng [2 ]
Lang, Guangming [3 ]
机构：
[1] Natl Univ Def Technol, Coll Informat Syst & Management, Changsha 410073, Hunan, Peoples R China
[2] Cent South Univ Forestry & Technol, Coll Logist & Transportat, Changsha 410000, Hunan, Peoples R China
[3] Changsha Univ Sci & Technol, Sch Math & Comp Sci, Changsha 410114, Hunan, Peoples R China
来源：
2017 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY) | 2017年
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Fuzzy sets; Rough Sets; Granular Computing; Attribute Reducts; Fuzzy Covering; Related Family; DYNAMIC-SYSTEMS; ALGORITHM; OPERATORS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Attribute reduction is the most important tool in rough set theory. To extend the application range, many fuzzy rough set models have been proposed, but less effort has been made for attribute reduction. In this paper, we construct a new method based on related family to get attribute reducts for fuzzy beta-covering rough sets.
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页数：5
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