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Modeling heterogeneous multi-attribute emergency decision-making with Dempster-Shafer theory

Computers & industrial engineering, 2021
Liguo Fei, Yuqiang Feng, Hongli Wang
semanticscholar   +1 more source

Consensus reaching with dynamic expert credibility under Dempster-Shafer theory

Information Sciences, 2022
Zhen-hong Hua, Liguo Fei, Huifeng Xue
semanticscholar   +1 more source

Dempster-Shafer Theory in Recommender Systems: A Survey

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Due to the limitations associated with the use of a single type of data during the recommendation process, recent research has focused on developing new fusion-based recommenders that make use of multiple heterogeneous sources of information to provide more accurate suggestions.
Khadidja Belmessous   +4 more
openaire   +1 more source

Some convergence results in Dempster-Shafer theory

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2002
Belief functions and basic probability assignments defined on a finite frame of discernment are given an intuitive extension. Some convergence results are then given on sets converging from above and below; also, a weakened form of one of the Borel-Cantelli lemmas is given. The paper concludes with a theorem on the Dempster-Shafer random variable.
openaire   +1 more source

Developing a Ship Collision Risk Index estimation model based on Dempster-Shafer theory

, 2021
Misganaw Abebe   +4 more
semanticscholar   +1 more source

Dempster-Shafer and Possibility Theory

2016
The last chapter presents an application of a particular class of normalized capacities (belief and plausibility measures) to the representation of uncertainty. This class has very specific properties and can be obtained through very different approaches (upper and lower probabilities, evidence theory and random sets, at least).
openaire   +1 more source

Dempster-Shafer Evidential Theory

2009
Dempster-Shafer evidential theory, a probability-based data fusion classification algorithm, is useful when the sensors (or more generally, the information sources) contributing information cannot associate a 100 percent probability of certainty to their output decisions.
openaire   +1 more source

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