Research On Power Transmission And Transformation Project Cost Control Methods Based On The Analysis Of Change Fitting

Power transmission project has features of wide coverage, uncertain design and construction conditions and so on. And these factors of uncertainty increase the difficulty of controlling power engineering cost in some certain extent. In addition, design, bidding, construction and other sectors are relatively independent in the process of transmission and substation engineering implementation, which makes it hard to do overall control of the cost.In order to realize the further refinement of cost control in the process of power transmission project construction, using the influence of different engineering change causes to power engineering cost, select representative engineering change indexes with the matter element model. From a quantitative perspective, with the help of the multivariate linear regression and RBF neural network combination fitting prediction model, establish the function relation between the influence factors of engineering changes and the cost of changes from the two aspects of linear and nonlinear, and use the alteration index selected to forecast the sum cost of engineering cost.Through the comparisons of single fitting prediction models and the combination model, embodies the superiority of combination model in fitting and prediction of engineering changes, simultaneously supporting the representation of change factors selected.Finally, according to the fitting and prediction results,propose the control methods for the main reasons which have a big affects on project cost.The combination model of multivariate linear regression and RBF neural network has a certain reference significance in other areas of prediction. According to the fitting and prediction results, the cost control method proposed according to different causes of power engineering cost has a strong guiding significance in the actual process of power transmission project construction.