Rough boundary entropy for measuring uncertainty of information system

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (28): 147-149.

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Rough boundary entropy for measuring uncertainty of information system

SHAN Xuehong1，2, WU Tao3, GAO Xiancai1，2

1.Laboratory of Intelligent Information Processing, Suzhou University, Suzhou, Anhui 234000, China
2.School of Mathematics & Statistics, Suzhou University, Suzhou, Anhui 234000, China
3.School of Mathematical Sciences, Anhui University, Hefei 230039, China

Online:2012-10-01 Published:2012-09-29

信息系统不确定性的粗糙边界熵度量方法

单雪红1，2，吴涛3，高显彩1，2

1.宿州学院智能信息处理实验室，安徽宿州 234000
2.宿州学院数学与统计学院，安徽宿州 234000
3.安徽大学数学科学学院，合肥 230039

Abstract

Abstract: Uncertainty measure is one of important contents of rough set theory study. In this paper, by analyzing the problem of methods for measuring the uncertainty of rough set, the rough boundary entropy is defined, based on boundary region. It is proved that the rough boundary entropy decreases monotonously as the knowledge granularity becomes finer. When the knowledge granularity of negative region is subdivided, the rough boundary entropy doesn’t change. Two properties of rough boundary entropy are given.

Key words: rough set, information system, uncertainty measure, rough boundary entropy, roughness, boundary region

摘要： 不确定性度量是粗糙集理论研究的重要内容之一。分析了目前粗糙集不确定性度量主要方法的不足，给出了基于边界域的粗糙集粗糙边界熵的定义。证明了这种粗糙边界熵随着知识粒度的减小而单调减小，而且当负域的知识颗粒被细分时，粗糙边界熵不变。给出了粗糙边界熵的两条性质。

关键词: 粗糙集, 信息系统, 不确定性度量, 粗糙边界熵, 粗糙度, 边界域

SHAN Xuehong1，2, WU Tao3, GAO Xiancai1，2. Rough boundary entropy for measuring uncertainty of information system[J]. Computer Engineering and Applications, 2012, 48(28): 147-149.

单雪红1，2，吴涛3，高显彩1，2. 信息系统不确定性的粗糙边界熵度量方法[J]. 计算机工程与应用, 2012, 48(28): 147-149.

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Rough boundary entropy for measuring uncertainty of information system

信息系统不确定性的粗糙边界熵度量方法

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