A new divergence measure for belief functions in D-S evidence theory for multisensor data fusion
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Publication:2660721
DOI10.1016/j.ins.2019.11.022zbMath1457.68268OpenAlexW2986647026WikidataQ126798640 ScholiaQ126798640MaRDI QIDQ2660721
Publication date: 31 March 2021
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2019.11.022
belief functionDempster-Shafer evidence theorymultisensor data fusionbelief divergence measureevidential conflict
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Cites Work
- Evidential reasoning rule for evidence combination
- Functions defined on a set of Z-numbers
- The general theory of decisions
- Zero-sum polymatrix games with link uncertainty: a Dempster-Shafer theory solution
- Uncertainty measurement with belief entropy on the interference effect in the quantum-like Bayesian networks
- An evidential Markov decision making model
- R-numbers, a new risk modeling associated with fuzzy numbers and its application to decision making
- QUANTIFICATION OF CONFLICT IN DEMPSTER-SHAFER FRAMEWORK: A NEW APPROACH
- Upper and Lower Probabilities Induced by a Multivalued Mapping
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