The Bayesian network method is introduced into the process of fire risk quantitative assessment. The event tree model is established, and the Bayesian network model is transformed from the event tree model based on the typical fire scenarios in high-rise space. A Bayesian fire risk assessment algorithm for high-rise buildings based on mutual information reliability is proposed. Bayesian network is modified considering the influence of uncertainties. Finally, the modified Bayesian network model is used to calculate the probability of fire developing to different stages, and the estimated value of property loss is used to express the severity of the accident and calculate the fire risk value. The results show that the existence of uncertainties has a significant impact on the results of risk assessment; the quantitative assessment method based on Bayesian network is better than the ETA method based on event tree analysis in dealing with uncertainties and is more suitable for high-rise space fire risk assessment.
Study on fire risk assessment for underwater soft rock tunnels based on AHP