On the fusion of imprecise uncertainty measures using belief structures

DOI10.1016/j.ins.2011.02.010zbMath1216.68297OpenAlexW2030795651MaRDI QIDQ545388

Ronald R. Yager

Publication date: 22 June 2011

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2011.02.010

zbMATH Keywords

uncertaintynormalizationmulti-source fusionDempster-Shafer

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (9)

A unified framework for characterizing rough sets with evidence theory in various approximation spaces ⋮ Consistency of probability decision rules and its inference in probability decision table ⋮ Sequential covariance intersection fusion Kalman filter ⋮ Maintenance policy performance assessment in presence of imprecision based on Dempster-Shafer theory of evidence ⋮ An information fusion approach by combining multigranulation rough sets and evidence theory ⋮ A general evidential reasoning algorithm for multi-attribute decision analysis under interval uncertainty ⋮ A belief function theory based approach to combining different representation of uncertainty in prognostics ⋮ Generalized combination rule for evidential reasoning approach and Dempster-Shafer theory of evidence ⋮ Dynamic systems based on preference graph and distance

Cites Work

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• Theory of capacities
• On the problem of retranslation in computing with perceptions
• ENTROPY AND SPECIFICITY IN A MATHEMATICAL THEORY OF EVIDENCE
• On the unicity of dempster rule of combination
• Upper and Lower Probabilities Induced by a Multivalued Mapping
• New Methods for Reasoning Towards Posterior Distributions Based on Sample Data
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