Haku
Viitteet 1-9 / 9
Machine learning for assessing chloride resistance of concrete
(2022)
Predicting the chloride resistance property of concrete accurately is critical in structural engineering. This thesis project adopts a state-of-the-art machine learning algorithm, XGBoost, to predict the chloride migration ...
Cow Dung Ash in Mortar: An Experimental Study
(MDPI AG, 2023)
Unveiling non-steady chloride migration insights through explainable machine learning
(Elsevier BV, 2024)
This study explores the influence of concrete mix ingredients on the non-steady chloride migration coefficient () using an explainable machine learning (XML) approach that integrates Extreme Gradient Boosting (XGBoost) and ...