Event tree,fault tree,decision-making tree and Bayesian network
XU Zhi-yong · Journal of Hohai University · 2009
Based on an introduction to the Bayesian network and the analysis of three examples,an event tree of a dam failure,a fault tree for unexpected ignition of a missile engine,and a decision-making tree for sale of cars,the methods of the event tree,the fault tree and the decision-making tree were compared with the Bayesian network.A general law was developed to translate the event tree,the fault tree and the decision-making tree into the Bayesian network.Firstly,in the Bayesian network the nodes denoted the events.Secondly,the nodes were connected with directed arcs according to the causality and influence of the events.Finally,the conditional probability table for the nodes was determined in terms of the given data or experts' experience.The results show that the Bayesian network has advantages in dealing with complex multi-state models and bi-directional reasoning.