A Variation of the Algorithm to Achieve the Maximum Entropy for Belief Functions [PDF]
Entropy, 2023 Evidence theory (TE), based on imprecise probabilities, is often more appropriate than the classical theory of probability (PT) to apply in situations with inaccurate or incomplete information.
Joaquín Abellán +2 more
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A New Correlation Measure for Belief Functions and Their Application in Data Fusion [PDF]
Entropy, 2023 Measuring the correlation between belief functions is an important issue in Dempster–Shafer theory. From the perspective of uncertainty, analyzing the correlation may provide a more comprehensive reference for uncertain information processing.
Zhuo Zhang +3 more
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Genetic Algorithm Based on a New Similarity for Probabilistic Transformation of Belief Functions [PDF]
Entropy, 2022 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 ...
Yilin Dong, Lei Cao, Kezhu Zuo
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Adaptive Belief Rule Base Modeling of Complex Industrial Systems Based on Sigmoid Functions [PDF]
EntropyIn response to the challenges posed by multifactorial nonlinear relationships and uncertainties, and to address the limitations of the existing Belief Rule Base (BRB) in nonlinear fitting, uncertainty representation, and parameter optimization, this ...
Haolan Huang +4 more
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The application of Dempster-Shafer theory demonstrated with justification provided by legal evidence [PDF]
Judgment and Decision Making, 2007 In forecasting and decision making, people can and often do represent a degree of belief in some proposition. At least two separate constructs capture such degrees of belief: likelihoods capturing evidential balance and support capturing evidential ...
Shawn P. Curley
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Diag-Skills: A Diagnosis System Using Belief Functions and Semantic Models in ITS
Applied Sciences, 2021 This work is related to the diagnosis process in intelligent tutoring systems (ITS). This process is usually a complex task that relies on imperfect data. Indeed, learning data may suffer from imprecision, uncertainty, and sometimes contradictions.
Nesrine Rahmouni +3 more
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Involutory Negator of Basic Belief Assignments
Cybernetics and Information Technologies, 2023 This paper analyzes the different definitions of a negator of a probability mass function (pmf) and a Basic Belief Assignment (BBA) available in the literature.
Dezert Jean, Tchamova Albena
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RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification
Applied Sciences, 2023 When radar receives target echoes to form plots, it is inevitably affected by clutter, which brings a lot of imprecise and uncertain information to target recognition.
Rui Yang, Yingbo Zhao, Yuan Shi
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Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used [PDF]
Yugoslav Journal of Operations Research, 2014 Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of
Cinicioglu Esma Nur
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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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