GRANULAR STRUCTURES OF FUZZY ROUGH SETS BASED ON GENERAL FUZZY RELATIONS

被引：0

作者：

Zhang, Xiao ^{[1
]}

Mei, Chang-Lin ^{[2
]}

Chen, De-Gang ^{[3
]}

机构：

[1] Xian Univ Technol, Sch Sci, Dept Appl Math, Xian, Peoples R China

[2] Xi An Jiao Tong Univ, Sch Math & Stat, Dept Stat, Xian 710049, Peoples R China

[3] North China Elect Power Univ, Dept Math & Phys, Beijing, Peoples R China

来源：

PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOL. 2 | 2015年

关键词：

Fuzzy relation; Fuzzy rough sets; Granular structure; ATTRIBUTE REDUCTION; DIAGNOSIS; SYSTEMS; MODEL;

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：

Existing studies on the granular structures of fuzzy rough sets are mainly proposed based on the T-similarity relations which are only a special kind of fuzzy relations. Therefore, it is of interest to extend the study to more general situations in order to expand the application scope of the fuzzy rough set theory. In this paper, the granular structures of the S-lower, T-upper, nu-lower and sigma-upper approximations of the fuzzy sets are established based on more general fuzzy relations.

引用

页码：832 / 837

页数：6

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