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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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Efficient Deep Wavelet Gaussian Markov Dempster–Shafer Network-Based Spectrum Sensing at Very Low SNR in Cognitive Radio Networks [PDF]
SensorsCognitive radio networks (CRNs) rely heavily on spectral sensing to detect primary user (PU) activity, yet detection at low signal-to-noise ratios (SNRs) remains a major challenge.
Sunil Jatti, Anshul Tyagi
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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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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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Human Cognitive Models for Heritage Site Monitoring
Digital Presentation and Preservation of Cultural and Scientific Heritage, 2021 Integrating evidence from a single sensor over time is becoming more common due to the Internet of Things (IoT). It can play a critical role in Heritage site monitoring, as networks of sensors are required to catalog and analyze data over extended ...
Michael E. Farmer
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