Italiano (Italian) English (Inglese)
domenica, 17 dicembre 2017


Dettagli Pubblicazione
Autori:Daniele Codetta Raiteri
Area Scientifica:Diagnosis
Probabilistic Graphical Models
Dependability and Reliability
Titolo:Applying Generalized Continuous Time Bayesian Networks to a reliability case study
Apparso su: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
Sommario: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.