This study explores the potential advantages of using multiple machine learning (ML) models to predict the baseline compressive strength (CS) and CS of SCM concrete subjected to chloride ingression. Four ML models, including Random Forest (RF), Gradient Boosting (GradBoost), Extreme Gradient Boosting (XgBoost), and Ada...
O. Ikponmwosa, A. A. Falade, Saheed Adedokun· Global Journal of Engineerin...· 0 citations
This study investigates the influence of hypersaline water on the compressive strength, bleeding, and water absorption of concrete, comparing freshwater and saltwater curing environments. Mixes were prepared using 0%, 10%, 15%, 20%, and 30% saltwater by weight of mixing water (0, 100, 150, 200, and 300 g/L of dissolved...
A. A. Falade, E. Nwankwo, S. Agboola et al.· Discover Concrete and Cement· 0 citations
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