Covering-based multi-granulation fuzzy rough sets

被引：20
作者：
Liu, Caihui [1 ,2 ]
Pedrycz, Witold [2 ,3 ]
机构：
[1] Gannan Normal Univ, Dept Math & Comp Sci, Ganzhou, Jiangxi, Peoples R China
[2] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB, Canada
[3] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2016年 / 30卷 / 01期
关键词：
Covering; exclusion; fuzzy rough sets; multi-granulation; reduct; FEATURE-SELECTION; ATTRIBUTE REDUCTION; APPROXIMATION OPERATORS; EXTRACTION; DUALITY;
D O I：
10.3233/IFS-151757
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As a new and meaningful extension of the Pawlak rough set, multi-granulation rough sets (MGRSs) have attracted much attention and fruitful achievements have been reported in different aspects. By combining with fuzzy rough set, the paper introduces multi-granulation fuzzy rough sets in the covering approximation space, namely, covering-based multi-granulation fuzzy rough sets (CMFRS), which form the extension of fuzzy rough sets. We first investigate several important properties of lower and upper approximations of concepts in covering-based multi-granulation fuzzy rough sets and elaborate on the differences between the proposed models and the existing ones in literature. By employing the notions of reduct and exclusion of a covering, the paper studies the necessary and sufficient conditions for two CMFRS to generate identical lower and upper approximations of a target concept in the given covering approximation space. Finally, the relationships between the new models are explored in the paper.
引用
收藏
页码：303 / 318
页数：16
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