Quantifying the uncertainty of information distributions containing randomness, imprecision,
and fuzziness is the premise of processing them. A useful information representation in the …

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 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 …

The increasing use of wireless sensor networks necessitates rapid detection and mitigation
of system anomalies and state changes, which can be achieved through change point …

The use of robotics in the process industry has shown a stable, increasing trend, according
to survey reports, reducing the exposure of operators to critical operations, mainly during …

Measuring the uncertainty of information is a crucial problem in many fields. Recent studies
have found a new uncertainty measure for probabilities called “extropy” as a complementary …

The hydraulic system is an integral part of CNC machine tools. In analyzing the reliability of
machine tool hydraulic systems, their failures are influenced by both aleatory and epistemic …

Evaluating the capabilities of a satellite communication system (SCS) is challenging due to
its complexity and ambiguity. It is difficult to accurately analyze uncertain situations, making it …

According to the generalized Jaccard coefficient and false degree, an improved approach is
proposed by incorporating Dempster-Shafer proofs for determining the level of confidence in …

While Evidence Theory (Demster-Shafer Theory, Belief Functions Theory) is being
increasingly used in data fusion, its potentialities in the Social and Life Sciences are often …