Estimation and prediction of construction cost index using neural networks, time series, and regression

Abstract

Estimating construction costs and predicting price escalation are major steps for project owners, estimators, and contractors. The construction costs are always subject to fluctuations that trend toward increasing over the long term, which make the pricing process challenging job. The construction cost index (CCI) has been widely used to forecast project costs. The problem is that no agency provides estimation for that important index in Egypt. In this paper, a formula is driven for calculating the Construction Cost Index for concrete structures based on past records of key construction costs. Neural Networks, Linear Regression, and Autoregressive Time Series are then utilized to forecast the CCI. The main contribution of this study is providing construction stakeholders with a reliable tool for expecting prices of coming projects, especially with the existing Rates of Inflation.