Uporedite metode

	Bajezijanska analiza stabla događaja	Analiza stabala događaja (ETA)
Oblast	Eksperimentalni dizajn	Pouzdanost
Porodica	Process / pipeline	Process / pipeline
Godina nastanka	ETA: 1960s–1970s; Bayesian extension: 1990s–2000s	2002
Tvorac	H.E. Watson (Bell Labs, fault tree); ETA formalized via US Nuclear Regulatory Commission; Bayesian extension developed in reliability and risk engineering communities	Andrews & Moss
Tip	Probabilistic risk and reliability analysis technique	Forward inductive logic tree
Temeljni izvor	Bearfield, G., & Marsh, W. (2005). Generalising event trees using Bayesian networks with a case study of train derailment. In G. Windeknecht et al. (Eds.), Proceedings of the 13th Safety-Critical Systems Symposium. Springer.	Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5
Drugi nazivi	Bayesian ETA, B-ETA, Probabilistic Event Tree Analysis, Bayesian Inductive Risk Model	ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi
Srodne	5	2
Sažetak	Bayesian Event Tree Analysis (B-ETA) is a quantitative risk assessment method that extends classical event tree analysis by incorporating Bayesian inference to assign and update branch probabilities. Starting from an initiating event, it maps sequences of successes and failures through safety barriers, using prior distributions and observed evidence to produce posterior outcome probabilities. Widely used in nuclear safety, process industries, and system reliability engineering.	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.