Project overheads estimation by applying a selected rate as a percentage of direct cost is used widely in bidding in construction, but the rate is prone to inaccuracy if it is selected subjectively. An improved approach is developed, a decision support system (DSS) based on a construction firm's...

Artificial neural networks, which simulate neuronal systems of the brain, are useful methods that have attracted the attention of researchers in many disciplinary areas. They have many advantages over traditional methods in situations where the input-output relationship of the system under study...

Neural network cost models have been developed using data collected from nearly 300 building projects. Data were collected from predominantly primary sources using real-life data contained in project files, with some data obtained from the Building Cost Information Service, supplemented with...

Neural network and regression models have been developed to predict the completed cost of competitively bid highway projects constructed by the New Jersey Department of Transportation. Bid information was studied for inclusion as inputs to the models. Data studied included the low bid, median...

The frequency of construction litigation has increased over the years, making litigation a costly and time-consuming activity. It is in the interests of all parties to a construction contract to avoid litigation. A tool (Ant Miner) is proposed to predict the outcome of construction litigation,...

In recent years, forecasting demand for residential construction in Singapore has become more vital, since it is widely perceived that the next trough of the real estate cycle is approaching. This paper evaluates the use of a combination of neural networks (NNs) and genetic algorithms (GAs) to...

Contractor pre-qualification can be regarded as a complicated, two-group, non-linear classification problem. It involves a variety of subjective and uncertain information extracted from various parties such as contractors, pre-qualifiers and project teams. Non-linearity, uncertainty and...