The main objective of this paper is to develop a systematic neural network model to estimate the conceptual cost for sustainable construction projects. A wide range of influencing factors on micro and macro level has been considered. The proposed engineering approach is pragmatic to model labour and material cost incurred in different stages of construction using the Artificial Neural Network (ANN) technique. The results indicated an acceptable convergence with reasonable generalization capabilities and the results obtained from the neural network model are more accurate and credible. This study contributes to the construction professionals by providing insight for using different ANN activation and transfer functions along with a wide range of influencing factors to benchmark the project manager’s conceptual cost predicting capabilities. Moreover, the systematic engineering approach guides the project managers how a readily available practical database can help optimize several objectives. It supports two key factors of sustainable construction: the economic dimension and the social dimension.
Digital Object Identifier (DOI)
S. Kumar, P. and Gururaj, S.
"Conceptual Cost Modelling for Sustainable Construction Project Planning— A Levenberg–Marquardt Neural Network Approach,"
Applied Mathematics & Information Sciences: Vol. 13:
2, Article 7.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol13/iss2/7