Prediction and Estimation of Highway Construction Cost using Machine Learning
Received: 2 July 2024 | Revised: 22 July 2024 | Accepted: 24 July 2024 | Online: 1 September 2024
Corresponding author: Raquim N. Zehawi
Abstract
Cost estimation and prediction are crucial processes for the success of construction projects, especially for infrastructure development. This study analyzes historical data collected between 2011 and 2023 and investigates the relationship between construction elements and the final cost of highway construction projects in Iraq. Different cost analysis approaches, including statistical assessment and machine learning techniques, were applied to a dataset of 291 highway projects. Cost estimation is a time-consuming and risky process that requires many qualitative and quantitative parameters to be well analyzed. However, machine learning provides a comprehensive assessment tool to predict future costs. Four ANN-based models were investigated and precision was improved by combining RMSE and the correlation coefficient (R) as a controller. The results showed improvements in performance metrics, such as error reduction rate and correlation coefficient, for the models developed. The best performance was achieved at an R of 0.989. The proposed model can be effectively adapted to predict road construction costs. Despite the need for more data, the implication of the proposed model can ensure a sustainable application, saving the time and resources required by construction professionals to predict road project costs during the planning phase.
Keywords:
ANN, cost prediction, machine learning, estimation, statistical analysisDownloads
References
N. I. El-Sawalhi and O. Shehatto, "A Neural Network Model for Building Construction Projects Cost Estimating," Journal of Construction Engineering and Project Management, vol. 4, no. 4, pp. 9–16, Dec. 2014.
A. Alkhuadhan and S. Naimi, "A new model for cost estimation construction project using Hybrid importance regression ensemble method," Acta logistica, vol. 10, no. 2, pp. 191–198, Jun. 2023.
S. Yun, "Performance Analysis of Construction Cost Prediction Using Neural Network for Multioutput Regression," Applied Sciences, vol. 12, no. 19, Jan. 2022, Art. no. 9592.
Y. Zhang, R. E. Minchin, I. Flood, and R. J. Ries, "Preliminary Cost Estimation of Highway Projects Using Statistical Learning Methods," Journal of Construction Engineering and Management, vol. 149, no. 5, May 2023, Art. no. 04023026.
M. G. Meharie, Z. C. A. Gariy, R. N. Ndisya Mutuku, and W. J. Mengesha, "An Effective Approach to Input Variable Selection for Preliminary Cost Estimation of Construction Projects," Advances in Civil Engineering, vol. 2019, no. 1, 2019, Art. no. 4092549.
C. R. Irnanda, I. Sadalia, and Nazaruddin, "Contract Analysis for Design and Build Lump Sum Price," presented at the 19th International Symposium on Management (INSYMA 2022), Dec. 2022, pp. 1162–1169.
A. O. Elfaki, S. Alatawi, and E. Abushandi, "Using Intelligent Techniques in Construction Project Cost Estimation: 10-Year Survey," Advances in Civil Engineering, vol. 2014, no. 1, 2014, Art. no. 107926.
B. J. Gardner, D. D. Gransberg, and H. D. Jeong, "Reducing Data-Collection Efforts for Conceptual Cost Estimating at a Highway Agency," Journal of Construction Engineering and Management, vol. 142, no. 11, Nov. 2016, Art. no. 04016057.
J. Yuan and C. Yin, "Cost Estimation of Expressway Construction and Installation Engineering Based on Convolutional Neural Networks," Journal of Engineering Studies, vol. 15, no. 5, pp. 446–455, Oct. 2023.
Y. G. Abed, T. M. Hasan, and R. N. Zehawi, "Cost Prediction for Roads Construction using Machine Learning Models," International Journal of Electrical and Computer Engineering Systems, vol. 13, no. 10, pp. 927–936, Dec. 2022.
Y. Zhang, R. E. Minchin, I. Flood, and R. J. Ries, "Preliminary Cost Estimation of Highway Projects Using Statistical Learning Methods," Journal of Construction Engineering and Management, vol. 149, no. 5, May 2023, Art. no. 04023026.
M. G. Meharie, W. J. Mengesha, Z. A. Gariy, and R. N. N. Mutuku, "Application of stacking ensemble machine learning algorithm in predicting the cost of highway construction projects," Engineering, Construction and Architectural Management, vol. 29, no. 7, pp. 2836–2853, Jan. 2022.
S. H. Ji, J. Ahn, H. S. Lee, and K. Han, "Cost Estimation Model Using Modified Parameters for Construction Projects," Advances in Civil Engineering, vol. 2019, no. 1, 2019, Art. no. 8290935.
S. Yun, "Performance Analysis of Construction Cost Prediction Using Neural Network for Multioutput Regression," Applied Sciences, vol. 12, no. 19, Jan. 2022, Art. no. 9592.
G. I. Parisi, R. Kemker, J. L. Part, C. Kanan, and S. Wermter, "Continual lifelong learning with neural networks: A review," Neural Networks, vol. 113, pp. 54–71, May 2019.
G. M. Tina, C. Ventura, S. Ferlito, and S. De Vito, "A State-of-Art-Review on Machine-Learning Based Methods for PV," Applied Sciences, vol. 11, no. 16, Jan. 2021, Art. no. 7550.
J. C. Ancheta et al., "Road construction analysis using regression technique," World Journal of Advanced Research and Reviews, vol. 18, no. 3, pp. 658–664, 2023.
A. F. Khalil and S. Rostam, "Machine Learning-based Predictive Maintenance for Fault Detection in Rotating Machinery: A Case Study," Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13181–13189, Apr. 2024.
A. Satty, M. M. Y. Salih, A. A. Hassaballa, E. A. E. Gumma, A. Abdallah, and G. S. M. Khamis, "Comparative Analysis of Machine Learning Algorithms for Investigating Myocardial Infarction Complications," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12775–12779, Feb. 2024.
L. Gurung and M. Chhetri, "Cost estimation model for highway projects using ANN," Zorig Melong- A Technical Journal of Science, Engineering and Technology, vol. 8, no. 1, Jun. 2023.
A. M. Abd and S. S. Sammen, "Artificial Neural Network Model for Managing and Forecasting Water Reservoir Discharge (Hemren Reservoir as A Case Study)," Diyala Journal of Engineering Sciences, pp. 132–143, Dec. 2014.
D. O. Mac-Barango and P. C. Nwogu, "Ranking of Variables Influencing Construction Project," World Journal of Finance and Investment Research, vol. 6, no. 1, pp. 49–61, Aug. 2022.
C. Magashi, J. Agbinya, A. Sam, and J. Mbelwa, "Prediction of SACCOS Failure in Tanzania using Machine Learning Models," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12887–12891, Feb. 2024.
Downloads
How to Cite
License
Copyright (c) 2024 Abbas M. Abd, Yassir A. Kareem, Raquim N. Zehawi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
