Cost Estimation of Civil Construction Projects using Machine Learning Paradigm

Adequate construction cost estimation is main factor in any type of construction projects. Forecasting cost of construction projects can be considered as difficult task. In this paper, Ordinary Least Square (OLS) method which is type ofa simple linear regression model is proposed to forecast future cost of construction projects. Ordinary Least Square method can be used to produce best solution and performs well when the dataset is small. Experiments were performed with 12 years of District Schedule Rates of Pune region from India to find out the accuracy of the model. The results show that proposed model gives 91% to 97% prediction accuracy.