Machine learning-driven prediction of compressive strength in sustainable geopolymer concrete using artificial neural network and random forest models
ABSTRACT Geopolymer concrete is a sustainable substitute for ordinary Portland cement which minimizes carbon dioxide emissions and effectively utilizes the waste from industries. Proper predictive estimating compressive strength can assist in the mix deign optimization, structural reliability. The article presents a ma...