Belief functions theory (BFT) plays a critical role in addressing uncertainty and imprecision in
multi-source data fusion. Unfortunately, the application of Dempster's rule in BFT often …

Abstract Dempster–Shafer (D–S) evidence theory is useful in the realm of multi-source data
fusion. However, a counterintuitive result may be obtained when the belief probability …

Multi-source information fusion technology has been widely used because it can maximize
the use of information that collected from multiple data sources for decision fusion. As an …

Abstract Dempster–Shafer (D–S) evidence theory is useful for handling uncertainty
problems in multisensor data fusion. However, the question of how to handle highly …

How to manage conflict in Dempster–Shafer (DS) evidence theory is still an open problem.
To address this problem, a novel divergence measure is proposed to measure the distance …

Divergence measure is widely used in many applications. To efficiently deal with uncertainty
in real applications, basic probability assignment (BPA) in Dempster-Shafer evidence …

Abstract Dempster-Shafer theory (DST), as a generalization of Bayesian probability theory,
is a useful technique for achieving multi-source information fusion under uncertain …

Dempster-Shafer evidence theory (DSET) has a wide and important application in
information fusion. However, when the pieces of evidence are highly conflicting, Dempster's …

Multi-source information fusion is a sophisticated estimation process that generates a unified
profile to assess complex situations. Dempster–Shafer evidence theory (DSET) is a practical …

Dempster–Shafer theory is invaluable for handing uncertain problems in multisource
information fusion field. But how to fuse highly conflicting information remains a pending …