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A computer-based cost prediction model for institutional building projects in Nigeria: An artificial neural network approach

Kabir Bala (Department of Building, Faculty of Environmental Design, Ahmadu Bello University, Zaria, Nigeria)
Shehu Ahmad Bustani (Department of Building, Faculty of Environmental Design, Ahmadu Bello University, Zaria, Nigeria)
Baba Shehu Waziri (Department of Civil and Water Resources Engineering, University of Maiduguri, Maiduguri, Nigeria)

Journal of Engineering, Design and Technology

ISSN: 1726-0531

Article publication date: 30 September 2014

462

Abstract

Purpose

The purpose of this study was develop a computer-based cost prediction model for institutional building projects in Nigeria through the use of artificial neural network (ANN) technique. The back-propagation network learns by example and provides good prediction to novel cases.

Design/methodology/approach

The input variables were derived from related works with modification and advices from professionals through a field survey. Two hundred and sixty completed project data were used for training and development of the ANN model. Back-propagation algorithm using the gradient descent delta learning rule with a learning coefficient of 0.4 was used. The input layer of the model comprised of nine variables; building height, compactness of building, construction duration, external wall area, gross floor area, number of floors, proportion of opening on external walls, location index and time index.

Findings

Several multi-layer perceptron networks were developed with varying architecture from which the network 9-7-5-1 was selected. The performance of the model over the validation sample revealed that the model has a mean absolute per cent error of 5.4 per cent and average error of prediction of −2.5 per cent over the sample. The ANN model was considered to be effective for construction cost prediction.

Research limitations/implications

The model may not be suitable for other building types because of the uniqueness of such facility even though significant difference is not anticipated for buildings such as commercial and residential. The models were evaluated based on the prediction errors; other means of evaluation were not used.

Originality/value

The study thus provides a simple, yet effective means of predicting construction costs of institutional building projects in Nigeria using an ANN model.

Keywords

Citation

Bala, K., Ahmad Bustani, S. and Shehu Waziri, B. (2014), "A computer-based cost prediction model for institutional building projects in Nigeria: An artificial neural network approach", Journal of Engineering, Design and Technology, Vol. 12 No. 4, pp. 519-530. https://doi.org/10.1108/JEDT-06-2012-0026

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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