Mathematical Foundations of Probabilistic Estimation in Fuzzy Bayesian Belief Networks

Specific problems arising in the creation of Bayesian networks for processing fuzzy information are considered. Conditions are obtained that ensure the probabilistic correctness of a priori data and results of network computing. For the case of nondeterministic states of network vertices, a fuzzy li...

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Veröffentlicht in:Cybernetics and systems analysis Jg. 52; H. 2; S. 206 - 218
Hauptverfasser: Parasyuk, I. M., Verovka, O. V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.03.2016
Springer
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Bayesian analysis
Belief networks
Computer science
Control
Cybernetics
Estimates
Fuzzy
Fuzzy logic
Interpolation
Mathematics
Mathematics and Statistics
Networks
Probabilistic methods
Probability
Probability theory
Processor Architectures
Software Engineering/Programming and Operating Systems
Studies
Systems Theory
fuzzy probability estimate
correctness of fuzzy computations
binary network
nondeterministic state
Bayesian belief network
ISSN:1060-0396, 1573-8337
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Zusammenfassung:Specific problems arising in the creation of Bayesian networks for processing fuzzy information are considered. Conditions are obtained that ensure the probabilistic correctness of a priori data and results of network computing. For the case of nondeterministic states of network vertices, a fuzzy linear interpolation procedure is proposed. The presented results make it possible to perform correct probabilistic Bayesian estimation over fuzzy networks of any configuration.
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ISSN:1060-0396
1573-8337
DOI:10.1007/s10559-016-9816-3