Artificial Neural Networks for Construction Management: A Review

Abstract

Construction Management (CM) has to deal with a variety of uncertainties related to Time, Cost, Quality and Safety, to name a few. Such uncertainties make the entire construction process highly unpredictable. It therefore falls under the purview of artificial neural networks (ANNs) in which the given hazy information can be effectively interpreted in order to arrive at meaningful conclusions. This paper reviews application of ANNs in construction activities related to prediction of costs, risk and safety, tender bids, as well as labor and equipment productivity. The review suggests that the ANN's had been highly beneficial in correctly interpreting an inadequate input information. It was seen that most of the investigators used feed forward back propagation type of the network; however if a single ANN architecture was found to be insufficient then hybrid modeling in association with other machine learning tools such as genetic programming and support vector machines were much useful. It was however clear that the authenticity of data and experience of the modeler are important in obtaining good results.