Pessimistic rough set based decisions: A multigranulation fusion strategy

被引:149
|
作者
Qian, Yuhua [1 ]
Li, Shunyong [2 ]
Liang, Jiye [1 ]
Shi, Zhongzhi [3 ]
Wang, Feng [1 ]
机构
[1] Shanxi Univ, Minist Educ, Key Lab Computat Intelligence & Chinese Informat, Taiyuan 030006, Shanxi, Peoples R China
[2] Shanxi Univ, Sch Comp & Informat Technol, Taiyuan 030006, Shanxi, Peoples R China
[3] Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
关键词
Rough set; Granular computing; Multigranulation; Pessimistic rough set based decision; Attribute reduction; INFORMATION GRANULATION; REDUCTION; APPROXIMATION; ACQUISITION; UNCERTAINTY; SYSTEM; RULES; MODEL;
D O I
10.1016/j.ins.2013.12.014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Multigranulation rough sets (MGRS) is one of desirable directions in rough set theory, in which lower/upper approximations are approximated by granular structures induced by multiple binary relations. It provides a new perspective for decision making analysis based on rough set theory. In decision making analysis, people often adopt the decision strategy "Seeking common ground while eliminating differences" (SCED). This strategy implies that one reserves common decisions while deleting inconsistent decisions. From this point of view, the objective of this study is to develop a new multigranulation rough set based decision model based on SCED strategy, called pessimistic multigranulation rough sets. We study this model from three aspects, which are lower/upper approximation and their properties, decision rules and attribute reduction, in this paper. (C) 2013 Published by Elsevier Inc.
引用
收藏
页码:196 / 210
页数:15
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