Open access
Jun 2026
Explainable Hybridized Machine Learning for Prediction of Compressive Strength of Fly-Ash based Geopolymer Concrete
This study utilizes robust machine learning (ML) techniques to predict compressive strength of fly-ash-based geopolymer concrete (GPC), a sustainable replacement for traditional concrete. Popular ensemble models, specifically Random Forest (RF) and Extreme Gradient Boosting (XGB), were taken as base models and were hyb...
Subodh Subedi, Ajaya Subedi, S. Adhikari et al.
· Bulletin of Computational In... · 1 citation