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A model utilizing the artificial neural network in cost estimation of construction projects in Jordan

Dareen Ryied Al-Tawal (Department of Civil Engineering, The University of Jordan, Amman, Jordan)
Mazen Arafah (Department of Industrial Engineering, The University of Jordan, Amman, Jordan)
Ghaleb Jalil Sweis (Department of Civil Engineering, The University of Jordan, Amman, Jordan)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 10 December 2020

Issue publication date: 2 November 2021

592

Abstract

Purpose

Cost estimation is one of the most significant steps in construction planning, which must be undertaken in the preliminary stages of any project; it is required for all projects to establish the project's budget. Confidence in these initial estimates is low, primarily due to the limited availability of suitable data, which leads the construction projects to frequently end up over budget. This paper investigated the efficacy of artificial neural networks (ANNs) methodologies in overcoming cost estimation problems in the early phases of the building design process.

Design/methodology/approach

Cost and design data from 104 projects constructed over the past five years in Jordan were used to develop, train and test ANN models. At the detailed design stage, 53 design factors were utilized to develop the first ANN model; then the factors were reduced to 41 and were utilized to develop the second predictive model at the schematic design stage. Finally, 27 design factors available at the concept design stage were utilized for the third ANN model.

Findings

The models achieved average cost estimation accuracy of 98, 98 and 97% in the detailed, schematic and concept design stages, respectively.

Research limitations/implications

This paper formulated the aims and objectives to be applicable only in Jordan using historical data of building projects.

Originality/value

The ANN approach introduced as a management tool is expected to provide the stakeholders in the engineering business with an indispensable tool for predicting the cost with limited data at the early stages of construction projects.

Keywords

Citation

Al-Tawal, D.R., Arafah, M. and Sweis, G.J. (2021), "A model utilizing the artificial neural network in cost estimation of construction projects in Jordan", Engineering, Construction and Architectural Management, Vol. 28 No. 9, pp. 2466-2488. https://doi.org/10.1108/ECAM-06-2020-0402

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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