NEURAL NETWORK APPLICATION FOR BUILDING PROJECTS COST ESTIMATION (Journal of Engineering, 2011)
This work presents a neural network based cost estimating method, developed for the generationof conceptual cost estimates for total building and electromechanical systems in building project,by using eight parameters available at the early design phase. This model establishes amethodology that can provide an economical and rapid means of cost estimating. Eighteen lighrise building projects, built between 1996 and 2009 in Middle East countries used in this study.The performance of developed cost models was tested against costs incurred by projects not usedin training of those models. Results show the mean absolute percentage errors (MAPE) arebetween 1.51% and 4.771 % for the five networks, and the maximum/minimum deviation of thecost estimation is 10.2/0.17. These figures considered good cost estimation at the early designstage.