Abu-Mahfouz, E; Al-Dahidi, S; Gharaibeh, E and Alahmer, A (2025) A novel feature engineering-based hybrid approach for precise construction cost estimation using fuzzy-AHP and artificial neural networks. International Journal of Construction Management, 25(15), pp. 1800-1810. ISSN 1562-3599
Abstract
The integration of Artificial Intelligence (AI) into construction cost estimation is transforming the way engineers tackle complex challenges. AI algorithms play a pivotal role in predicting project costs by scrutinizing historical data from previous construction projects. This study introduces a novel hybrid approach combining the Fuzzy-Analytic Hierarchy Process (F-AHP) and Artificial Neural Networks (ANNs) to enhance the accuracy of construction cost estimations. The F-AHP identifies the most influential features affecting project costs and assigns appropriate weights, while the ANN captures the intricate and 'unknown' mathematical relationships between these features and the corresponding costs. The approach was validated using real-world data from 96 residential and specialized housing projects in Amman, Jordan spanning from 2014 to 2021. Eleven key features are selected to train the ANN prediction model. To enhance prediction accuracy, the ANN model is optimized in terms of training/learning algorithms, hidden-neuron activation functions and the number of hidden neurons. The Qusai Newton, an exponential linear unit (Elu) function and 8 neurons were identified, respectively, as the optimal configuration, based on standard accuracy metrics. This optimized setup yields a Root Mean Square Error of 31,000 JD, a Mean Absolute Percentage Error of 3% and a maximum Coefficient of Determination of 98%.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural network; construction projects; cost prediction; feature engineering; fuzzy-analytic hierarchy process; housing companies |
| Index terms: | learning algorithm, construction project, Amman, artificial intelligence, artificial neural network, construction cost, housing project, Jordan, integration, estimation, cost prediction, configuration, prediction model, engineer, accuracy, mean square error, housing, project cost |
| Subjects: | prediction and forecasting, modelling and simulation, construction type, economics, profession, production management, algorithms, probability and distributions, financial and cost management, housing and residential development, Geography, artificial intelligence, systems engineering, professional development, organizational analysis |
| Topics: | Cost Management, Geographical Context, Urban Studies, Information Management, Organizational Design, Construction Technology, Engineering Principles, Project Management, Digital Applications, Roles and Professions, Research Practice |
| Descriptive scope: | 3 PCA |
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