Linearity is considered as a fundamental property of significant importance in numerous
domains. A linear mathematical expression is clear, concise, and convenient for solving …

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 …

Dempster's rule of combination (DRC) is widely used for uncertainty reasoning in intelligent
information system, which is generalized to complex domain recently. However, as the …

Multisource data fusion analysis, particularly in decision-level fusion strategies, is emerging
for application in real-life scenarios. The Dempster–Shafer evidence theory (DSET) is a …

Abstract The Dempster-Shafer (DS) evidence theory, renowned for its efficacy in processing
uncertain information, has garnered substantial attention in recent decades. A generalized …

Divergence could be used to quantify the difference between two probability distributions.
However, how to accurately quantify the disparity between evidences remains a pending …

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 …

Belief functions as a powerful model to represent and deal with uncertain information are
widely used in information fusion. However, semantic association within a frame of …

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