Rough set approach under dynamic granulation in incomplete information systems

被引：2
|
作者：
Qian, Yuhua [1 ,2 ,3 ]
Liang, Jiye [1 ,2 ]
Zhang, Xia [1 ,2 ]
Dang, Chuangyin [3 ]
机构：
[1] Shanxi Univ, Sch Comp & Informat Technol, Taiyuan 030006, Shanxi, Peoples R China
[2] Minist Educ, Key Lab Computat Intelligence & Informat Proc, Taiyuan 030006, Peoples R China
[3] City Univ Hong Kong, Dept Mfg Engn & Engn Management, Hong Kong, Peoples R China
来源：
MICAI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE | 2007年 / 4827卷
基金：
中国国家自然科学基金;
关键词：
information systems; granular computing; dynamic granulation; partial relation;
D O I：
10.1109/MILCOM.2007.4455050
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the concept of a granulation order is proposed in an incomplete information system. Positive approximation of a set under a granulation order is defined and its some useful properties are investigated. Unlike classical rough set, this approach focuses on how to describe the structure of a rough set in incomplete information systems. For a subset of the universe, its approximation accuracy is monotonously increasing under a granulation order. This means that a proper family of granulations can be chosen for a target-concept approximation according to user requirements.
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页码：1 / +
页数：3
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