Research On The Risk Assessment Of The Project Group Based On The Bayesian Network

With the development of project management, more and more modernenterprises view multi-project operations as the main mode of operation. For theseenterprises, because of the limited resources, their projects will be different in quality,cost, progress and other aspects, which will be a big risk. Therefore, the key tosuccess of these enterprises is the ability of quickly identifying, evaluating andcontrolling the risk. Fast and accurate project risk evaluation is becoming one of thekey technologies influencing the agility and competitiveness of enterprises. How toevaluate the risk quickly and accurately in a multi-project environment, so as to laythe foundation of risk control, is a problem worth further study.This paper uses the knowledge of Bayesian network to build the system of groupproject risk assessment which is based on Bayesian network for risk evaluation of thegroup project in multi project environment. Firstly, On the basis of the knowledge offuzzy rough set, this paper constructs the Project Group Work Breakdown StructureModeling. At the same time, standardization of project elements are programmed, andan example is used to demonstrate the feasibility of the model, which not only meetthe customer’s needs of creating a work breakdown structure quickly, efficiently andinexpensively, but also lay the foundation for risk identification in project group.Secondly, based on the Project Group Work Breakdown Structure Modeling, weidentify the risk and construct the system of risk evaluation index of project group.Then, in this paper, according to the system of risk evaluation index of project groupand based on the related knowledge of Bayesian, the Bayesian network topology isconstructed and the nodes of network structure are set and assigned. Then we use thesoftware for Bayesian network reasoning to determine the posterior probability of thenodes, so as to establish risk assessment of the project group based on the Bayesiannetwork.Finally, in chapter5, we do simulation experiments by using MSBNxsoftware to verify the feasibility of risk assessment of the project group based on theBayesian network in the first two chapters.The research results of this paper enriches and expands the theory and method ofrisk evaluation in multi project environment theoretically, and provides a validreference for the risk assessment and management of multi project operationenterprises. Thus, this research is of great significance both theoretically and practically.