Results 21 to 30 of about 13,623,354 (322)
Depth-bounded Belief functions
International Journal of Approximate Reasoning, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
P. Baldi, H. Hosni
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Frontiers in Psychology, 2022 This study investigated relationships between inter-class variations in paranormal experience and executive functions. A sample of 516 adults completed self-report measures assessing personal encounter-based paranormal occurrences (i.e., Experience ...
Kenneth Graham Drinkwater +4 more
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Two Applications of Inter-Criteria Analysis with Belief Functions
Cybernetics and Information Technologies, 2020 In this paper we present two applications of a new Belief Function-based Inter-Criteria Analysis (BF-ICrA) approach for the assessment of redundancy of criteria involved in Multi-Criteria Decision-Making (MCDM) problems.
Dezert Jean +3 more
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On properties of a new decomposable entropy of Dempster-Shafer belief functions
International Journal of Approximate Reasoning, 2020 We define entropy of belief functions in the Dempster-Shafer (D-S) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannon's definitions of entropy and conditional entropy for probability mass ...
R. Jirousek, Prakash P. Shenoy
semanticscholar +1 more source
A New Image Registration Algorithm Based on Evidential Reasoning
Sensors, 2019 Image registration is a crucial and fundamental problem in image processing and computer vision, which aims to align two or more images of the same scene acquired from different views or at different times.
Zhe Zhang +3 more
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Hidden Conflicts of Belief Functions
International Journal of Computational Intelligence Systems, 2020 In this paper, hidden conflicts of belief functions are observed in the case where the sum of all multiples of the conflicting belief masses equals zero.
Milan Daniel, Václav Kratochvíl
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Second-Order Belief Hidden Markov Models [PDF]
, 2014 Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model.
A. Aregui +17 more
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An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions [PDF]
International Journal of Approximate Reasoning, 2019 The main goal of this paper is to describe an axiomatic utility theory for Dempster-Shafer belief function lotteries. The axiomatic framework used is analogous to von Neumann-Morgenstern's utility theory for probabilistic lotteries as described by Luce ...
T. Denoeux, Prakash P. Shenoy
semanticscholar +1 more source
Approximated Computation of Belief Functions for Robust Design Optimization [PDF]
, 2012 This paper presents some ideas to reduce the computational cost of evidence-based robust design optimization. Evidence Theory crystallizes both the aleatory and epistemic uncertainties in the design parameters, providing two quantitative measures, Belief
A. +10 more
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Credible Information, Allowable Information and Belief Revision - Extended Abstract [PDF]
Electronic Proceedings in Theoretical Computer Science, 2019 In an earlier paper [Rational choice and AGM belief revision, Artificial Intelligence, 2009] a correspondence was established between the choice structures of revealed-preference theory (developed in economics) and the syntactic belief revision ...
Giacomo Bonanno
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