Research On The Target Cost Forecast And Control Of Construction Project

In recent years, with the rapid development of the Reform and Opening-up andcontinuous improvement of the national economy, construction enterprises in China hasimproved production capacity as well as found their new production requirements,however, the development of China’s project management theory and practice is still slowly.The traditional project cost management mode and system has exposed many deficiencies inmodern project management, these deficiencies have seriously hampered the boomingdevelopment of our construction industry, restricting the improvement of our economy aswell. Therefore, the new construction project cost management methods and modes worthy ofour careful research and discussion.On the basis of in-depth study on the construction project management theory, this paperattempt to research on the application of Regression analysis and Bayesian network in projectcost management. By means of the advantage of Regression analysis in refining capacity fromhistorical data and the capacity of Bayesian network in uncertainty analysis, to research on theproject cost forecast and control. The paper prove the effectiveness of two methods in costmanagement by an engineering example, hope to offer help to improve and enhance the levelof construction enterprises cost management.Firstly, this paper introduces the target cost and cost control theory as well as analyzesthe shortage of traditional project cost management on the basis of summarizing the researchsituation that studied at home and abroad. According to the status of project cost managementfield in China, the new cost management theory were studied in this paper.Secondly, According to the different problems in project cost management, puts forwarda new solution respectively. In terms of cost forecast, we introduced the theory of Regressionanalysis and the general steps of the theory to establishment the cost forecast model.Regression analysis has strong objectivity, and can extract information from historical dataprecisely, at the same time, it can easy to use, in addition it has a good repeatability, that is tosay,it can be used in other field. Therefore, the process can be spread in constructionenterprises, and it shall bring about realistic impact. In terms of cost control, for the weaknessof The traditional control methods in the prior control, we used Bayesian network to solve thisproblem. By means of the function of Bayesian Networks in diagnosis, that is to say, it hasability to find the reasons according to the results. Before the construction start, we assumingthe target cost has changed, then identify the factors that affect the cost based on theassumption, to realize our purpose in cost control through controlling the impact of factors.Finally, we applied the models in the actual case, and proved the validity of the model.