Research Of The International High Speed Rail Project’s Schedule Risk Warning Based On Bayesian Network

Currently,"Chinese high-speed rail " is developing rapidly,as our country paying high attention to The high-speed rail and promoting it vigorously,at present we have cooperated with many countries including Turkey,Indonesia,Thailand,Russia,and so on,"The high-speed rail goes out" is not only the output of The high-speed rail’s technology,but also bringing more investment project for participants.International high-speed rail project has the characteristics of long construction period and complex project environment,if project schedule cannot be effectively controlled,it will cause construction costs to increase,and let the contractor face a huge compensation because they are unable to fulfill the terms of the contract,so how to control project schedule has become a major problem for contractors of our country.Until now,there is not a lot of researches on the schedule’s risk warning of the international high-speed rail project at home and abroad.In order to achieve the target of changing the ex post processing into early warning,it is important to establish accurate and practical schedule’s risk warning model of international high-speed rail project.Firstly,this paper collects as much as possible risk factors affecting international high-speed rail project through the analysis of historical documents,then select the risk factors that affect the schedule of the project through brainstorming method,and make additions and deletions appropriately,form a list of schedule’s risk factors of the international high-speed rail project.On this basis,using the method of questionnaire to investigate and study the risk factors,and select the risk factors for the construction of the early warning index system through data analysis results.Next to determine the schedule’s risk warning interval and use the risk matrix to standardize the data of each risk index,based on the data after normalization,using GeNIe2.0 software to learn Bayesian network structure and conduct parameter learning,then through the analysis of causal relationships between various risk factors to modify the network model to get a more accurate Bayesian network model.Then,this paper carries on the reverse reasoning,the sensitive inference and the maximum causal chain analysis and derives important and sensitive risk factors from reasoning results.Further,the corresponding countermeasures are put forward for the project with different risk levels,the main risk factors and the dynamic risk factors.Finally,the model is applied to Turkey high-speed rail project(Ankara to Istanbul),through practice to verify the feasibility and practicality of the early warning model.