A survey: Optimization and applications of evidence fusion algorithm based on Dempster–Shafer theory

K Zhao, L Li, Z Chen, R Sun, G Yuan, J Li - Applied Soft Computing, 2022 - Elsevier
Abstract Since Dempster–Shafer evidence theory was proposed, it has been widely and
successfully used in many fields including risk analysis, fault diagnosis, wireless sensor …

[HTML][HTML] Representing uncertainty and imprecision in machine learning: A survey on belief functions

Z Liu, S Letchmunan - Journal of King Saud University-Computer and …, 2024 - Elsevier
Uncertainty and imprecision accompany the world we live in and occur in almost every
event. How to better interpret and manage uncertainty and imprecision play a vital role in …

Generalized divergence-based decision making method with an application to pattern classification

F **ao, J Wen, W Pedrycz - IEEE transactions on knowledge …, 2022 - ieeexplore.ieee.org
In decision-making systems, how to address uncertainty plays an important role for the
improvement of system performance in uncertainty reasoning. Dempster–Shafer evidence …

A complex weighted discounting multisource information fusion with its application in pattern classification

F **ao, Z Cao, CT Lin - IEEE transactions on knowledge and …, 2022 - ieeexplore.ieee.org
Complex evidence theory (CET) is an effective method for uncertainty reasoning in
knowledge-based systems with good interpretability that has recently attracted much …

Conflicting evidence combination from the perspective of networks

L **ong, X Su, H Qian - Information Sciences, 2021 - Elsevier
Dempster-Shafer evidence theory is widely used in the field of information fusion especially
when confronting with uncertainties. However, Dempster's rule of combination may lead to …

A novel quantum model of mass function for uncertain information fusion

X Deng, S Xue, W Jiang - Information Fusion, 2023 - Elsevier
Understanding the uncertainty involved in a mass function is a central issue in Dempster–
Shafer evidence theory for uncertain information fusion. Recent advances suggest to …

An effective conflict management method based on belief similarity measure and entropy for multi-sensor data fusion

Z Liu - Artificial Intelligence Review, 2023 - Springer
Multi-sensor data fusion has received substantial attention thanks to its ability to integrate
information from distinct sources efficiently. Nevertheless, the information collected from …

An optimization model for rescuer assignments under an uncertain environment by using Dempster–Shafer theory

L Fei, Y Wang - Knowledge-Based Systems, 2022 - Elsevier
Emergency decision making and disposal are significant challenges faced by the
international community. To minimize the emergency casualties, and reduce probable …

Higher order fractal belief Rényi divergence with its applications in pattern classification

Y Huang, F **ao, Z Cao, CT Lin - IEEE Transactions on Pattern …, 2023 - ieeexplore.ieee.org
Information can be quantified and expressed by uncertainty, and improving the decision
level of uncertain information is vital in modeling and processing uncertain information …

A novel conflict measurement in decision-making and its application in fault diagnosis

F **ao, Z Cao, A Jolfaei - IEEE Transactions on Fuzzy Systems, 2020 - ieeexplore.ieee.org
Dempster-Shafer evidence (DSE) theory, which allows combining pieces of evidence from
different data sources to derive a degree of belief function that is a type of fuzzy measure, is …