A Novel Measure of Uncertainty in the Dempster-Shafer Theory

被引：12
作者：
Wen, Ke [1 ,2 ]
Song, Yafei [3 ]
Wu, Chunhua [2 ]
Li, Tianpeng [4 ]
机构：
[1] Tsinghua Univ, Dept Mech Engn, Beijing 100084, Peoples R China
[2] PLA Air Force Xian Flight Acad, Xian 710306, Peoples R China
[3] Air Force Engn Univ, Air & Missile Def Coll, Xian 710051, Peoples R China
[4] PLA Strateg Support Army Informat Engn Univ, Inst Informat Syst Engn, Zhengzhou 450002, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Uncertainty; Measurement uncertainty; Entropy; Licenses; Probabilistic logic; Dispersion; Information theory; The Dempster-Shafer theory; measure of uncertainty; exponential function; validity and rationality; MEASURING AMBIGUITY; ENTROPY; INFORMATION; FRAMEWORK; FUSION;
D O I：
10.1109/ACCESS.2020.2979605
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the Dempster-Shafer theory, how to quantitatively evaluate the quality of information is an essential issue and also an open issue. Many of measures of uncertainty have been proposed in previous work, whereas some measures among them had been proved to have a few shortcomings. The validity and rationality of the measures proposed in recent years have been explored and analyzed preliminarily, and then an empirical measure of uncertainty with exponential function form which is directly based on the framework of the evidence theory is proposed to overcome the shortcomings. Several numerical examples have been presented to illustrate the validity and rationality of the empirical measure.
引用
收藏
页码：51550 / 51559
页数：10
相关论文
共 58 条
[1]   Requirements for total uncertainty measures in Dempster-Shafer theory of evidence [J].
Abellan, Joaquin ;
Masegosa, Andres .
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2008, 37 (06) :733-747
[2]   Analyzing properties of Deng entropy in the theory of evidence [J].
Abellan, Joaquin .
CHAOS SOLITONS & FRACTALS, 2017, 95 :195-199
[3]  
[Anonymous], THESIS
[4]  
[Anonymous], [No title captured]
[5]  
[Anonymous], [No title captured]
[6]  
[Anonymous], [No title captured]
[7]  
Ben Hariz S, 2006, LECT NOTES COMPUT SC, V4183, P162
[8]   A novel weighted evidence combination rule based on improved entropy function with a diagnosis application [J].
Chen, Lei ;
Diao, Ling ;
Sang, Jun .
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2019, 15 (01)
[9]   On the plausibility transformation method for translating belief function models to probability models [J].
Cobb, BR ;
Shenoy, PP .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2006, 41 (03) :314-330
[10]   An Improved Deng Entropy and Its Application in Pattern Recognition [J].
Cui, Huizi ;
Liu, Qing ;
Zhang, Jianfeng ;
Kang, Bingyi .
IEEE ACCESS, 2019, 7 :18284-18292
123456