基于贝叶斯网络的空间受限项目风险管理研究

Research on Risk Management of Space-limited Project Based on Bayesian Network

空间受限项目的事故风险源多,且易诱发连锁反应。如何快速识别空间受限项目的风险源,并有效评估各个诱发节点的风险大小,对空间受限项目的风险管理具有重要意义。识别空间受限项目风险源并构造贝叶斯网络,通过贝叶斯网络推理的正向预测、反向诊断,获得各个风险源节点的后验概率,并计算风险源概率与事故发生的互信息,同时引入风险可控值概念及指标量化,构建基于贝叶斯网络的二维四区风险管理模型,提出空间受限项目风险源管理策略,最后通过一个实例对研究结果进行说明。

There are various risk resources- of accident in space-limited project, and easily cause relative chain reactions. It is significant for risk management of space-limited project to rapidly identify risk sources and effectively get assessment of the risk of.each induced accident node. Authors identify risk sources of space-limited project and construct a Bayesian Network risk model to get the posterior probability of each risk source node which uses Bayesian Network＇ s forward prediction and backward diagnosis. Then authors calculate the mutual information of probability of risk source and accident, introduce a concept of controllable and quantified value of risk sources to construct Two- dimensional ＆ Four-zones （TDFZ） risk management model based on mutual information, and propose corresponding management strategies. Finally, authors explain the research result through an example.