Predicting the Duration of a General Contracting Industrial Project based on the Residual Modified Model

摘要

The general contracting projects are developed in China, in the past two decades. In the early stage of a project, because of the lack of specific design drawings and project plans, it is difficult for the general contractor to determine the construction period when signing the contract. However, little research has undertaken on quickly and efficiently estimating construction duration of a general contracting industrial project. Therefore, the purpose of this paper is to explore a suitable model for estimating construction duration of the general contracting industrial project in China. Data for 90 completed projects are collected in a company that undertakes nationwide industrial projects. Four single variable models and fourteen multivariate models are analyzed using statistical method. And the residual modified model integrating wavelet neural network (WNN) is also developed through using a predictive error to amend the statistical model. The results show that the residual modified models obtain more enhanced prediction accuracy than regression models, despite their good fitting performance. The modified model can be used for helping contractors forecast project duration in the early stage of a project.