Predicting Production Rates of Egyptian Bricklayers Using Artificial Neural Networks and Regression Models

AbstractConstruction production rates are affected by several factors. The impact of different factors on construction labor productivity can be quantified by productivity models. Therefore, the first objective of this study is to identify and quantify the impact of different factors on the production rates of Egyptian bricklayers (PREB). The second objective is to develop three models to predict the PREB. Two models were developed using statistical regression analysis and were backward and forward regression model (BRM and FRM). The third model was developed using artificial neural networks(ANNs). Therefore, a fundamental question arises: which technique of them provides better closeness to data fit and better prediction performance.