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

How to handle conflict in Dempster-Shafer evidence theory is an open issue. Many
approaches have been proposed to solve this problem. The existing approaches can be …

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 …

Uncertainty modeling and reasoning in intelligent systems are crucial for effective decision-
making, such as complex evidence theory (CET) being particularly promising in dynamic …

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 …

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

Uncertainty quantification of belief functions is an unsolved issue in belief function theory
that is used widely to tackle epistemic uncertainty. This study provides a new definition of …

An enhanced evidence theory‐based multisensor data fusion technique is presented to
address the problem of poor data fusion caused by an unknown interference in the fully …

The safe navigation of unmanned surface vehicles in the marine environment requires multi-
sensor collaborative perception, and multi-sensor data fusion technology is a prerequisite …