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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 …
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
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 …
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
In decision-making systems, how to address uncertainty plays an important role for the
improvement of system performance in uncertainty reasoning. Dempster–Shafer evidence …
improvement of system performance in uncertainty reasoning. Dempster–Shafer evidence …
A complex weighted discounting multisource information fusion with its application in pattern classification
Complex evidence theory (CET) is an effective method for uncertainty reasoning in
knowledge-based systems with good interpretability that has recently attracted much …
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 …
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 …
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 …
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
Emergency decision making and disposal are significant challenges faced by the
international community. To minimize the emergency casualties, and reduce probable …
international community. To minimize the emergency casualties, and reduce probable …
Higher order fractal belief Rényi divergence with its applications in pattern classification
Information can be quantified and expressed by uncertainty, and improving the decision
level of uncertain information is vital in modeling and processing uncertain information …
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
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 …
different data sources to derive a degree of belief function that is a type of fuzzy measure, is …