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Thursday, 29 February 2024


Pubblication Details
Authors:Daniele Codetta Raiteri
Scientific Area:Diagnosis
Probabilistic Graphical Models
Dependability and Reliability
Title:Applying Generalized Continuous Time Bayesian Networks to a reliability case study
Published on:Proceedings of the International Symposium on Fault Detection, Supervision and Safety of Technical Processes, IFAC-PapersOnLine, vol. 48(21)
Tipo Pubblicazione:Paper on Proceedings International Conference
Abstract:We discuss the main features of Generalized Continuous Time Bayesian Networks (GCTBN) as a reliability formalism: we resort to a specific case study taken from the literature, and we discuss modeling choices, analysis results and advantages with respect to other formalisms. From the modeling point of view, GTCBN can represent dependencies involving system components, together with the possibility of a continuous time evaluation of the model. From the analysis point of view, any task ascribable to a posterior probability computation can be implemented, such as the computation of system unreliability, importance (sensitivity) indices, system state prediction and diagnosis.