Paper Info
Title
Required Mathematical Properties And Behaviors Of Uncertainty Measures On Belief Intervals
Abstract
The Dempster-Shafer theory of evidence (DST) has been widely used to handle uncertainty-based information. It is based on the concept of basic probability assignment (BPA). Belief intervals are easier to manage than a BPA to represent uncertainty-based information. For this reason, several uncertainty measures for DST recently proposed are based on belief intervals. In this study, we carry out a study about the crucial mathematical properties and behavioral requirements that must be verified by every uncertainty measure on belief intervals. We base on the study previously carried out for uncertainty measures on BPAs. Furthermore, we analyze which of these properties are satisfied by each one of the uncertainty measures on belief intervals proposed so far. Such a comparative analysis shows that, among these measures, the maximum of entropy on the belief intervals is the most suitable one to be employed in practical applications since it is the only one that satisfies all the required mathematical properties and behaviors.
Year
DOI
Venue
2021
10.1002/int.22432
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
DocType
Volume
behavioral requirements, belief intervals, conflict, mathematical properties, non&#8208, specificity, uncertainty measures
Journal
36
Issue
ISSN
Citations 
8
0884-8173
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Serafín Moral-García104.06
Joaquin Abellan29110.99