RETRACTED: Cost prediction of building projects using the novel hybrid RA-ANN model
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 24 January 2023
Issue publication date: 10 June 2024
Retraction notice
The publisher of Engineering, Construction and Architectural Management wishes to retract the article Wang, Y., Zuo, J., Pan, M., Tu, B., Chang, R.-D., Liu, S., Xiong, F. and Dong, N. (2024), “Cost prediction of building projects using the novel hybrid RA-ANN model”, Engineering, Construction and Architectural Management, Vol. 31 No. 6, pp. 2563-2582. https://doi.org/10.1108/ECAM-07-2022-0666. It has come to our attention that there are concerns with the data used, specifically that the journal was not able to replicate the results of the analyses described; as a result the findings cannot be relied on. The authors of this article would like to note that they do not agree with the content of this notice. The publisher of the journal sincerely apologizes to the readers.
Abstract
Purpose
Accurate and timely cost prediction is critical to the success of construction projects which is still facing challenges especially at the early stage. In the context of rapid development of machine learning technology and the massive cost data from historical projects, this paper aims to propose a novel cost prediction model based on historical data with improved performance when only limited information about the new project is available.
Design/methodology/approach
The proposed approach combines regression analysis (RA) and artificial neural network (ANN) to build a novel hybrid cost prediction model with the former as front-end prediction and the latter as back-end correction. Firstly, the main factors influencing the cost of building projects are identified through literature research and subsequently screened by principal component analysis (PCA). Secondly the optimal RA model is determined through multi-model comparison and used for front-end prediction. Finally, ANN is applied to construct the error correction model. The hybrid RA-ANN model was trained and tested with cost data from 128 completed construction projects in China.
Findings
The results show that the hybrid cost prediction model has the advantages of both RA and ANN whose prediction accuracy is higher than that of RA and ANN only with the information such as total floor area, height and number of floors.
Originality/value
(1) The most critical influencing factors of the buildings’ cost are found out by means of PCA on the historical data. (2) A novel hybrid RA-ANN model is proposed which proved to have the advantages of both RA and ANN with higher accuracy. (3) The comparison among different models has been carried out which is helpful to future model selection.
Keywords
Citation
Wang, Y., Zuo, J., Pan, M., Tu, B., Chang, R.-D., Liu, S., Xiong, F. and Dong, N. (2024), "RETRACTED: Cost prediction of building projects using the novel hybrid RA-ANN model", Engineering, Construction and Architectural Management, Vol. 31 No. 6, pp. 2563-2582. https://doi.org/10.1108/ECAM-07-2022-0666
Publisher
:Emerald Publishing Limited
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