A numerical comparative study of uncertainty measures in the Dempster-Shafer evidence theory

被引：18

作者：

Urbani, Michele ^{[1
]}

Gasparini, Gaia ^{[1
]}

Brunelli, Matteo ^{[1
]}

机构：

[1] Univ Trento, Dept Ind Engn, Via Sommar 9, I-38123 Trento, Italy

来源：

INFORMATION SCIENCES | 2023年 / 639卷

关键词：

Evidence theory; Uncertainty measure; Entropy; Similarity; MEASURING AMBIGUITY; ENTROPY; INFORMATION;

D O I：

10.1016/j.ins.2023.119027

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider a wide range of measures of uncertainty that have been proposed within the Dempster-Shafer evidence theory. All these measures aim to quantify the uncertainty associated with a given basic probability assignment. As a preliminary step, we offer a study of the literature, which shows a recent resurgence of interest in the quantification of uncertainty in the evidence theory. Then, we compare a number of uncertainty measures by means of numerical simulations and analyze their similarities and differences using rank correlation coefficients, hierarchical clustering, and centrality analysis. The results show that uncertainty measures with similar formulations do not necessarily have similar numerical properties, and some original results are obtained. In particular, we demonstrate that numerical studies on uncertainty measures are necessary to obtain more insight and to enhance the interpretability of the values returned by the measures.

引用

页数：16

共 50 条

[1] Critique of Recent Uncertainty Measures Developed Under the Evidence Theory and Belief Intervals [J].