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Liang, M. (author), Chang, Z. (author), Wan, Z. (author), Gan, Y. (author), Schlangen, E. (author), Šavija, B. (author)
This study aims to provide an efficient and accurate machine learning (ML) approach for predicting the creep behavior of concrete. Three ensemble machine learning (EML) models are selected in this study: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient Boosting Machine (LGBM). Firstly, the creep data in...
journal article 2022