Comparer des méthodes

	Réseau bayésien	Arbre d'événements (ETA)
Domaine	Bayésien	Fiabilité
Famille	Bayesian methods	Process / pipeline
Année d'origine	1988	2002
Auteur d'origine	Judea Pearl	Andrews & Moss
Type	Probabilistic graphical model	Forward inductive logic tree
Source fondatrice	Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797	Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5
Alias	Bayes network, belief network, probabilistic graphical model, directed graphical model	ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi
Apparentées	4	2
Résumé	A Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others.	Event Tree Analysis (ETA) is a forward inductive technique used in reliability and risk engineering to model the possible outcomes that follow an initiating event. Starting from a single undesired event, ETA traces all subsequent event sequences through a binary branching tree representing the success or failure of safety barriers and protective systems. Introduced formally in reliability and risk literature by Andrews and Moss (2002), it is widely applied in nuclear, chemical, and aerospace industries to quantify accident sequence probabilities and guide safety decision-making.