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Related papers: A correlation coefficient of belief functions

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We first show that there are practical situations in for instance forensic and gambling settings, in which applying classical probability theory, that is, based on the axioms of Kolmogorov, is problematic. We then introduce and discuss…

Probability · Mathematics 2015-12-07 Timber Kerkvliet , Ronald Meester

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is…

Artificial Intelligence · Computer Science 2017-04-07 Mieczysław Kłopotek

While Evidence Theory (also known as Dempster-Shafer Theory, or Belief Functions Theory) is being increasingly used in data fusion, its potentialities in the Social and Life Sciences are often obscured by lack of awareness of its…

Artificial Intelligence · Computer Science 2025-03-31 Guido Fioretti

One of the most important aspects in any treatment of uncertain information is the rule of combination for updating the degrees of uncertainty. The theory of belief functions uses the Dempster rule to combine two belief functions defined by…

Artificial Intelligence · Computer Science 2013-04-05 Michael S. K. M. Wong , P. Lingras

This paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations…

Artificial Intelligence · Computer Science 2007-05-23 M. C. Florea , J. Dezert , P. Valin , F. Smarandache , Anne-Laure Jousselme

Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest. While existing correlation measures are suitable for discovering average correlation, they fail to discover hidden or…

Machine Learning · Statistics 2017-11-22 Hyeji Kim , Weihao Gao , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

In the interpretation of experimental data, one is actually looking for plausible explanations. We look for a measure of plausibility, with which we can compare different possible explanations, and which can be combined when there are…

Artificial Intelligence · Computer Science 2010-12-30 Wan Ahmad Tajuddin Wan Abdullah

We introduce measures of quantum coherence as the speed of evolution of a system under decoherence. That is, coherence is the ability to estimate a dephasing channel, quantified by the quantum Fisher information. We extend the analysis to…

Quantum Physics · Physics 2019-01-23 Benjamin Yadin , Pieter Bogaert , Cristian E. Susa , Davide Girolami

We first discuss certain problems with the classical probabilistic approach for assessing forensic evidence, in particular its inability to distinguish between lack of belief and disbelief, and its inability to model complete ignorance…

Probability · Mathematics 2017-02-02 Timber Kerkvliet , Ronald Meester

Correlation testing provides a quick method of discriminating amongst potential terms to include in a nuclear mass formula or functional and is a necessary tool for further nuclear mass models; however a firm mathematical foundation of the…

Nuclear Theory · Physics 2013-05-14 M. G. Bertolli

In this paper, we generalize the basic notions and results of Dempster-Shafer theory from predicates to formal concepts. Results include the representation of conceptual belief functions as inner measures of suitable probability functions,…

Artificial Intelligence · Computer Science 2021-05-19 Sabine Frittella , Krishna Manoorkar , Alessandra Palmigiano , Apostolos Tzimoulis , Nachoem M. Wijnberg

Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic probability assignments(BPAs) presents a measure of performance…

Artificial Intelligence · Computer Science 2014-04-15 Meizhu Li , Qi Zhang , Xinyang Deng , Yong Deng

When using complex Bayesian models to combine information, the checking for consistency of the information being combined is good statistical practice. Here a new method is developed for detecting prior-data conflicts in Bayesian models…

Methodology · Statistics 2016-11-29 David J. Nott , Xueou Wang , Michael Evans , Berthold-Georg Englert

Combining evidence from different sources can be achieved with Bayesian or Dempster-Shafer methods. The first requires an estimate of the priors and likelihoods while the second only needs an estimate of the posterior probabilities and…

Machine Learning · Computer Science 2021-04-16 Fabrice Daniel

As a generalization of Dempster-Shafer theory, D number theory provides a framework to deal with uncertain information with non-exclusiveness and incompleteness. However, some basic concepts in D number theory are not well defined. In this…

Artificial Intelligence · Computer Science 2019-12-03 Xinyang Deng

Data gathered from multiple sensors can be effectively fused for accurate monitoring of many engineering applications. In the last few years, one of the most sought after applications for multi sensor fusion has been fault diagnosis.…

Artificial Intelligence · Computer Science 2020-02-11 Nimisha Ghosh , Sayantan Saha , Rourab Paul

The theory of belief functions manages uncertainty and also proposes a set of combination rules to aggregate opinions of several sources. Some combination rules mix evidential information where sources are independent; other rules are…

Artificial Intelligence · Computer Science 2015-03-18 Mouna Chebbah , Arnaud Martin , Boutheina Ben Yaghlane

Correlation function and mutual information are two powerful tools to characterize the correlations in a quantum state of a composite system, widely used in many-body physics and in quantum information science, respectively. We find that…

Quantum Physics · Physics 2015-05-19 R. X. Dong , D. L. Zhou

Mathematical Theory of Evidence called also Dempster-Shafer Theory (DST) is known as a foundation for reasoning when knowledge is expressed at various levels of detail. Though much research effort has been committed to this theory since its…

Artificial Intelligence · Computer Science 2017-07-14 Mieczysław A. Kłopotek

This paper describes a natural framework for rules, based on belief functions, which includes a repre- sentation of numerical rules, default rules and rules allowing and rules not allowing contraposition. In particular it justifies the use…

Artificial Intelligence · Computer Science 2013-04-05 Nic Wilson