Bayesian Networks In The Application Of Uncertainty Risk Decision Research

In the face of the decision problem, the uncertainty can not be ignored, rather thanuncertainty causes from the problem, it also come from fuzziness, randomness, informationincompleteness and limitations of human cognitive ability.Therefore, in decision making,how to deal with these uncertainties become an important research content of thedecision-making.In this paper, research work as follows:First of all, in the Bayesian network concept, the uncertainty in the initial stage ofproject development risk of analysis to identify the potential risk of uncertainty and findrelationships of corresponding source of risk, the merger are listed in the list of risks.Secondly, the uncertainty of risk decision-making model based on Bayesian networks,and elaborated the theory and analysis of the model, the analysis process is divided intothree steps: risk identification process, the process of risk analysis and risk assessmentprocess. Combined with the analytic hierarchy process to assess the effects on risk factors.Finally, an example of real estate development to validate the established model forpracticality. Listed by the uncertainty of the real estate development project risk analysis.to use of expert knowledge given Bayesian network and related data. Bayesian networkinference to draw the corresponding risk probability of occurrence, combined with theweight of risk factors obtained by the analytic hierarchy process, and finally arrive at acomprehensive assessment of the uncertain risks. This can help managers to effectivelyavoid project risk, targeted to high-risk part to improve the stability of the entire projectprocess.