Information Entropy and Information Granulation-based Uncertainty Measures in Incomplete Information Systems

被引：3
|
作者：
Sun, Lin [1 ,2 ,3 ]
Xu, Jiucheng [1 ,2 ]
Xu, Tianhe [1 ,2 ]
机构：
[1] Henan Normal Univ, Coll Comp & Informat Engn, Xinxiang 453007, Peoples R China
[2] Engn Technol Res Ctr Comp Intelligence & Data Min, Xinxiang, Henan Province, Peoples R China
[3] Beijing Univ Technol, Int WIC Inst, Beijing 100124, Peoples R China
来源：
APPLIED MATHEMATICS & INFORMATION SCIENCES | 2014年 / 8卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Rough set; incomplete information system; information entropy; information granulation; uncertainty measure; FEATURE-SELECTION; KNOWLEDGE REDUCTION; ROUGH ENTROPY; ALGORITHM; SETS;
D O I：
10.12785/amis/080466
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, concepts of information entropy and information granulation-based uncertainty measures are introduced in incomplete information/decision systems, and based on maximal consistent block technique, some variants of information entropy and information granulation are presented to measure the discernibility ability of an incomplete information system. Then, some important properties of them are discussed. From these properties, it can be shown that these proposed measures provide important approaches to measure the uncertainty ability of different knowledge in incomplete information/decision systems. And relationships among these measures are established as well. These results will be very helpful for understanding the essence of knowledge content and uncertainty measures in incomplete information systems.
引用
收藏
页码：2073 / 2083
页数：11
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