Author:
Dong Yilin,Cao Lei,Zuo Kezhu
Abstract
Recent studies of alternative probabilistic transformation (PT) in Dempster–Shafer (DS) theory have mainly focused on investigating various schemes for assigning the mass of compound focal elements to each singleton in order to obtain a Bayesian belief function for decision-making problems. In the process of such a transformation, how to precisely evaluate the closeness between the original basic belief assignments (BBAs) and transformed BBAs is important. In this paper, a new aggregation measure is proposed by comprehensively considering the interval distance between BBAs and also the sequence inside the BBAs. Relying on this new measure, we propose a novel multi-objective evolutionary-based probabilistic transformation (MOEPT) thanks to global optimizing capabilities inspired by a genetic algorithm (GA). From the perspective of mathematical theory, convergence analysis of EPT is employed to prove the rationality of the GA used here. Finally, various scenarios in evidence reasoning are presented to evaluate the robustness of EPT.
Funder
Natural Nature Science Fund
Subject
General Physics and Astronomy
Reference39 articles.
1. Upper and lower probabilities induced by a multivalued mapping;Ann. Math. Stat.,1967
2. Shafer, G. (1976). A Mathematical Theory of Evidence, Princeton University Press.
3. Ambiguity-driven fuzzy C-means clustering: How to detect uncertainty clustered records;Appl. Intell.,2016
4. Combining dependent bodies of evidence;Appl. Intell.,2015
5. Inner and outer approximation of belief structures using a hierarchical clustering approach;Int. J. Uncertain. Fuzziness Knowl. Based Syst.,2001
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