Short-Interval Dynamic Forecasting for Actual S -Curve in the Construction Phase

Traditional approaches for cost forecasting tend to utilize a single model for the entire construction period. However, a construction project, consisting of different stages, will incur different costs, which may not be accurately captured by a single model. Gates separated the S-curve into three periods. Utilizing the same approach, the accuracy of cost forecasting can be improved by dividing the entire duration of a construction project into three periods. Therefore, this research aims at improving the traditional Grey prediction model by defining the suitable α instead of using 0.5. This new technique applies the golden section and bisection method to optimize α and build the short-interval cost-forecasting model. In each period of the construction phase, a customized optimization-forecasting model is used to estimate each short-interval cost. The proposed models should more closely predict the short-interval cost, which can be utilized to more accurately forecast the expenditure of the subsequent month within each period.