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A New Reliability Coefficient Using Betting Commitment Evidence Distance in Dempster–Shafer Evidence Theory for Uncertain Information Fusion [PDF]
Entropy, 2023 Dempster–Shafer evidence theory is widely used to deal with uncertain information by evidence modeling and evidence reasoning. However, if there is a high contradiction between different pieces of evidence, the Dempster combination rule may give a fusion
Yongchuan Tang +4 more
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Restricted Network Reconstruction from Time Series via Dempster–Shafer Evidence Theory [PDF]
EntropyAs a fundamental mathematical model for complex systems, complex networks describe interactions among social, infrastructural, and biological systems. However, the complete connection structure is often unobservable, making topology reconstruction from ...
Cai Zhang +4 more
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Identifying Influential Nodes Based on Evidence Theory in Complex Network [PDF]
EntropyInfluential node identification is an important and hot topic in the field of complex network science. Classical algorithms for identifying influential nodes are typically based on a single attribute of nodes or the simple fusion of a few attributes ...
Fu Tan +5 more
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Stock portfolio selection using Dempster–Shafer evidence theory
Journal of King Saud University: Computer and Information Sciences, 2018 Markowitz’s return–risk model for stock portfolio selection is based on the historical return data of assets. In addition to the effect of historical return, there are many other critical factors which directly or indirectly influence the stock market ...
Gour Sundar Mitra Thakur +2 more
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IEEE Access, 2021 Since the Dempster-Shafer evidence theory was developed, it has been extensively concerned by researchers. Compared with Bayesian probability theory, Dempster-Shafer evidence theory satisfies weaker constraints and has the advantage to indicate ...
Zichong Chen, Xianwen Luo
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A Networked Method for Multi-Evidence-Based Information Fusion
Entropy, 2022 Dempster–Shafer evidence theory is an effective way to solve multi-sensor data fusion problems. After developing many improved combination rules, Dempster–Shafer evidence theory can also yield excellent results when fusing highly conflicting evidence ...
Qian Liang, Zhongxin Liu, Zengqiang Chen
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A Novel Integration Method for D Numbers Based on Horizontal Comparison
Axioms, 2021 D numbers theory is an extension of Dempster–Shafer evidence theory. It eliminates the constraints of mutual exclusion and completeness under the frame of discernment of Dempster–Shafer evidence theory, so it has been widely used to deal with uncertainty
Haiyang Hou, Chunyu Zhao
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Evidence conflict measure based on OWA operator in open world. [PDF]
PLoS ONE, 2017 Dempster-Shafer evidence theory has been extensively used in many information fusion systems since it was proposed by Dempster and extended by Shafer.
Wen Jiang +4 more
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Applications of the Dempster-Shafer theory of evidence for simulation [PDF]
Proceedings of the 18th conference on Winter simulation - WSC '86, 1986 The Dempster-Shafer theory of belief functions shows promise as a means of incorporating incompleteness of evidence into simulation models. The key feature of the Dempster-Shafer theory is that precision in inputs is required only to a degree justified by available evidence.
Kathryn B. Laskey, Marvin S. Cohen
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IEEE Access, 2021 Multisensor data fusion is extensively used to merge data from heterogeneous sensors in a smart environment. However, sensors provide noisy and uncertain information which is a big challenge for researchers.
Ihsan Ullah, Joosang Youn, Youn-Hee Han
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