Assessing impacts of economic and municipality factors on building construction duration using ensemble categorical boosting

In addition to the need to increase the accuracy of models, there is a lack of consensus among researchers about considering factors of external economic in duration prediction models. First, the categorical boosting (CatBoost-2018) model in the first-level was created aiming to find the optimal combination of inputs with the best results for the duration. In continuation, only the second-level model i.e. Stacking-CatBoost2 model was created aiming to noticeably increase the estimation accuracy of two models of the first-level including the artificial neural network (ANN) single model and CatBoost1. The final stacking results also have shown the superiority of that model over three other study models according to the K-fold method (used for validation and verification). Then, the results of sensitivity analysis (SA) using the error deterioration measurement method have shown the negative impact of an economic input and the significant positive impact of a unique input to the project and three external economic factors.

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Publication Details

Journal
Discover Applied Sciences
Published
2025-05-25
DOI
https://doi.org/10.1007/s42452-025-07078-y
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
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article

Assessing impacts of economic and municipality factors on building construction duration using ensemble categorical boosting

Nasser Shahsavari-Pour, Mehdi Ravanshadnia, Mohammad Khalilzadeh, Farshad Peiman
Discover Applied Sciences
BIM and Construction Integration
article

Assessing impacts of economic and municipality factors on building construction duration using ensemble categorical boosting

Nasser Shahsavari-Pour, Mehdi Ravanshadnia, Mohammad Khalilzadeh, Farshad Peiman
article en

Abstract

In addition to the need to increase the accuracy of models, there is a lack of consensus among researchers about considering factors of external economic in duration prediction models. First, the categorical boosting (CatBoost-2018) model in the first-level was created aiming to find the optimal combination of inputs with the best results for the duration. In continuation, only the second-level model i.e. Stacking-CatBoost2 model was created aiming to noticeably increase the estimation accuracy of two models of the first-level including the artificial neural network (ANN) single model and CatBoost1. The final stacking results also have shown the superiority of that model over three other study models according to the K-fold method (used for validation and verification). Then, the results of sensitivity analysis (SA) using the error deterioration measurement method have shown the negative impact of an economic input and the significant positive impact of a unique input to the project and three external economic factors.

Discover Applied SciencesVol. 7(6)
Islamic Azad University South Tehran Branch (IR), Vali Asr University of Rafsanjan (IR), Pontificia Universidad Católica del Perú (PE)
Sustainable cities and communities
Openalex Percentile: Top 88%
BIM and Construction Integration
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