Information can be quantified and expressed by uncertainty, and improving the decision
level of uncertain information is vital in modeling and processing uncertain information …

It remains challenging in characterizing uncertain and imprecise information when clustering
fuzzy number data. To solve such a problem, this paper investigates a new credal-based …

Multisource information fusion is a comprehensive and interdisciplinary subject. Dempster-
Shafer (DS) evidence theory copes with uncertain information effectively. Pattern …

Complex evidence theory, a generalization of the Dempster-Shafer evidence theory, proves
to be effective in modeling and managing uncertainty within complex domains through the …

Complex evidence theory (CET), as a generalized DS evidence theory, has the ability to
express uncertainty in the complex field. CET has been applied in many information fields …

Abstract In Dempster-Shafer evidence theory, how to model and handle the uncertainty
involved in mass functions is generally concerned by researchers. Recently, a quantum …

Time series data contains the amount of information to reflect the development process and
state of a subject. Especially, the complexity is a valuable factor to illustrate the feature of the …

Dempster-Shafer evidence theory (DST) is a versatile framework for handling uncertainty
and provides a reliable method for data fusion. Managing conflicts between multiple bodies …

Dempster–Shafer evidence theory (DSET) is extensively employed in multi-source data
fusion applications. Nonetheless, when belief probability assignments (BPAs) exhibit …

In decision-making systems, conflict management is an important concept that represents
the degree of dissimilarity between bodies of evidence, ultimately enhancing decision …