Probability estimation is an integral part of risk analyses. This work intends to propose a probabilistic approach as a support system for risk assessment in order to establish a deeper understanding of accident causation pathways as a means for proposing improved preventive strategies, especially at the level of organizational and structural factors. This study addresses the problem of “damaging event” probability estimation with few statistics by the use of Knowledge Driven Bayesian Network (KDBN), that models the a priori knowledge of the risk context dynamics. Moreover the proposed approach aims at providing a quantitative methodological technique useful to monitor, prevent, and evaluate, and assess the risks at workplace.
PROBABILISTIC APPROACH AS A SUPPORT SYSTEM FOR SAFETY-CRITICAL ENVIRONMENTS BY KNOWLEDGE DRIVEN BAYESIAN NETWORKS
D'ELIA, Ciro;DE FELICE, Fabio;MARIANO, Paola;RUSCINO, Simona
2014-01-01
Abstract
Probability estimation is an integral part of risk analyses. This work intends to propose a probabilistic approach as a support system for risk assessment in order to establish a deeper understanding of accident causation pathways as a means for proposing improved preventive strategies, especially at the level of organizational and structural factors. This study addresses the problem of “damaging event” probability estimation with few statistics by the use of Knowledge Driven Bayesian Network (KDBN), that models the a priori knowledge of the risk context dynamics. Moreover the proposed approach aims at providing a quantitative methodological technique useful to monitor, prevent, and evaluate, and assess the risks at workplace.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
