<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Ensemble tree machine learning models have proved useful for solving poorly understood and complex problems. This paper aims to calibrate the Eurocode 2 creep model by inserting a correction coefficient to the model. The correction coefficient is calculated using ensemble tree (bagging and boosting) models. The results showed that the insertion of the correction coefficient obtained by both the bagging and boosting models into the Eurocode 2 model led to significantly higher prediction accuracy. These approaches may lead to a better performance prediction, thereby reducing the effect of the time-dependent deformation on concrete structures.</p>
</abstract>

Ensemble tree machine learning models have proved useful for solving poorly understood and complex problems. This paper aims to calibrate the Eurocode 2 creep model by inserting a correction coefficient to the model. The correction coefficient is calculated using ensemble tree (bagging and boosting) models. The results showed that the insertion of the correction coefficient obtained by both the bagging and boosting models into the Eurocode 2 model led to significantly higher prediction accuracy. These approaches may lead to a better performance prediction, thereby reducing the effect of the time-dependent deformation on concrete structures.

Ensemble Tree Machine Learning Models for Improvement of Eurocode 2 Creep Model Prediction

Civil and Environmental Engineering

This work is licensed under the Creative Commons Attribution 4.0 International License.

Ensemble tree machine learning models have proved useful for solving poorly understood and complex problems. This paper aims to calibrate the Eurocode 2 creep...

Ensemble Tree Machine Learning Models for Improvement of Eurocode 2 Creep Model Prediction

Online veröffentlicht: 29. Juni 2022

Seitenbereich: 174 - 184

DOI: https://doi.org/10.2478/cee-2022-0016

Schlüsselwörter
Ensemble tree, Bagging, Boosting, Creep, Eurocode 2

© 2022 Hikmat Daou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Ensemble Tree Machine Learning Models for Improvement of Eurocode 2 Creep Model Prediction

Online veröffentlicht: 29. Juni 2022

Seitenbereich: 174 - 184

DOI: https://doi.org/10.2478/cee-2022-0016

SchlüsselwörterEnsemble tree, Bagging, Boosting, Creep, Eurocode 2

© 2022 Hikmat Daou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Ensemble tree, Bagging, Boosting, Creep, Eurocode 2