Knowledge reduction in random information systems via Dempster-Shafer theory of evidence

被引：180
|
作者：
Wu, WZ [1 ]
Zhang, M
Li, HZ
Mi, JS
机构：
[1] Zhejiang Ocean Univ, Informat Coll, Zhoushan 316004, Zhejiang, Peoples R China
[2] Xi An Jiao Tong Univ, Natl Key Lab Mfg Syst Engn, Xian 710049, Peoples R China
[3] Xi An Jiao Tong Univ, Sch Management, Xian 710049, Peoples R China
[4] Hebei Normal Univ, Coll Math & Informat Sci, Shijiazhuang 050016, Hebei, Peoples R China
来源：
INFORMATION SCIENCES | 2005年 / 174卷 / 3-4期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
belief functions; consistent sets; decision systems; information systems; reducts; rough sets;
D O I：
10.1016/j.ins.2004.09.002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Knowledge reduction is one of the main problems in the study of rough set theory. This paper deals with knowledge reduction in (random) information systems based on Dempster-Shafer theory of evidence. The concepts of belief and plausibility reducts in (random) information systems are first introduced. It is proved that both of belief reduct and plausibility reduct are equivalent to classical reduct in (random) information systems. The relative belief and plausibility reducts in consistent and inconsistent (random) decision systems are then proposed and compared to the relative reduct and relationships between the new reducts and some existing ones are examined. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码：143 / 164
页数：22
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