Combination of interval-valued belief structures based on belief entropy

TL;DR

This paper introduces a new optimality approach for combining interval-valued belief structures using belief entropy, improving upon existing methods within Dempster-Shafer theory.

Contribution

It proposes a novel method based on uncertainty measures to enhance the combination and normalization of belief structures, addressing limitations of previous approaches.

Findings

The new approach effectively combines belief structures with improved rationality.

Numerical examples demonstrate the superiority of the proposed method.

The method offers a more optimal combination based on belief entropy.

Abstract

This paper investigates the issues of combination and normalization of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence. Existing approaches are reviewed and thoroughly analyzed. The advantages and drawbacks of previous approach are presented. A new optimality approach based on uncertainty measure is developed, where the problem of combining interval-valued belief structures degenerates into combining basic probability assignments. Numerical examples are provided to illustrate the rationality of the proposed approach.