A New Method of Attribute Reduction of Covering Rough Sets

被引：0

作者：

Yang, Tian ^{[1
]}

Li, Qingguo ^{[2
]}

Zhou, Bilei ^{[3
]}

机构：

[1] Cent South Univ Forestry & Technol, Coll Sci, Changsha 410004, Hunan, Peoples R China

[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

[3] Cent South Univ, Sch Business, Changsha 410083, Peoples R China

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC 2012) | 2012年

基金：

中国国家自然科学基金;

关键词：

Rough Sets; Granular Computing; Attribute Reducts; Covering; Related Family; FUZZY; APPROXIMATIONS; 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：

In rough set theory, the discernibility matrix is a classical method to compute all attribute reducts. However, it is useless in certain circumstances as shown in this paper. As a result, a new method, namely related family, is developed initially in this paper. As a more powerful tool than the discernibility matrix, relate family can compute all attribute reducts of covering generalized rough sets, not only in the cases the discernibility matrix is usually employed for, but also for more comprehensive instances to which the discernibility matrix is not applicable.

引用

页码：596 / 600

页数：5

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