Abstract
In this paper, we review briefly the different works published in the field of Dynamic Bayesian Network (DBN) reliability analyses and estimation, and we propose to use DBNs as a tool of knowledge extraction for constructing DBN models modeling the reliability of systems. This is doing, by exploiting the data of (tests or experiences feedback) taken from the history of the latter’s. The built model is used for estimating the system reliability via the inference mechanism of DBNs. The proposed approach has been validated using known system examples taken from the literature.
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Zahra, F.Z., Khouas-Oukid, S., Assoul-Semmar, Y. (2013). Dynamic Bayesian Networks in Dynamic Reliability and Proposition of a Generic Method for Dynamic Reliability Estimation. In: Amine, A., Otmane, A., Bellatreche, L. (eds) Modeling Approaches and Algorithms for Advanced Computer Applications. Studies in Computational Intelligence, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-319-00560-7_44
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DOI: https://doi.org/10.1007/978-3-319-00560-7_44
Publisher Name: Springer, Cham
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