Analyzing the monotonicity of belief interval based uncertainty measures in belief function theory

被引:87
|
作者
Deng, Xinyang [1 ]
机构
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
belief function; belief interval; Dempster-Shafer evidence theory; entropy; uncertainty measure; DEMPSTER-SHAFER THEORY; SPECIFICITY;
D O I
10.1002/int.21999
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Measuring the uncertainty of pieces of evidence is an open issue in belief function theory. A rational uncertainty measure for belief functions should meet some desirable properties, where monotonicity is a very important property. Recently, measuring the total uncertainty of a belief function based on its associated belief intervals becomes a new research idea and has attracted increasing interest. Several belief interval based uncertainty measures have been proposed for belief functions. In this paper, we summarize the properties of these uncertainty measures and especially investigate whether the monotonicity is satisfied by the measures. This study provide a comprehensive comparison to these belief interval based uncertainty measures and is very useful for choosing the appropriate uncertainty measure in the practical applications.
引用
收藏
页码:1869 / 1879
页数:11
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