Dynamic bayesian networks: Modeling problem

Seyed Mohammad Hadi Hosseini, Makoto Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new approach to apply dynamic relationships in dynamic Bayesian networks is presented. This model makes use of some of the concepts of functional event sequence diagrams for modeling dynamic relationships between component failures, physical variables, and measurements, and presents the required equations for derivation of conditional probability values to be automatically mapped into a temporal Bayesian networks. Using this approach, we can exploit expert knowledge for developing temporal BN and elicitation of required probability values more efficiently. The developed model using block diagrams will be also more informative and expressive. An application of this methodology is also presented for taking dynamic condition into account for diagnosis and prediction analysis.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Probabilistic Safety Assessment and Management, PSAM 2006
Publication statusPublished - 2006 Dec 1
Event8th International Conference on Probabilistic Safety Assessment and Management, PSAM 2006 - New Orleans, LA, United States
Duration: 2006 May 142006 May 18

Publication series

NameProceedings of the 8th International Conference on Probabilistic Safety Assessment and Management, PSAM 2006

Other

Other8th International Conference on Probabilistic Safety Assessment and Management, PSAM 2006
Country/TerritoryUnited States
CityNew Orleans, LA
Period06/5/1406/5/18

ASJC Scopus subject areas

  • Statistics and Probability

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