Application of Soft Computing Techniques to Predict the Strength of Geopolymer Composites.

ABSTRACT: Geopolymers may be the best alternative to ordinary Portland cement because they are manufactured using waste materials enriched in aluminosilicate. Research on geopolymer composites is accelerating. However, considerable work, expense, and time are needed to cast, cure, and test specimens. The application of computational methods to the stated objective is critical for speedy and cost-effective research. In this study, supervised machine learning approaches were employed to predict the compressive strength of geopolymer composites. One individual machine learning approach, decision tree, and two ensembled machine learning approaches, AdaBoost and random forest, were used. The coefficient correlation (R2), statistical tests, and k-fold analysis were used to determine the validity and compa

SUBMITTER: Wang Q 

PROVIDER: S-EPMC8956037 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature