Serwan Rafiq

Stacked-based machine learning to predict the uniaxial compressive strength of concrete materials

Developing fully recycled alkali-activated mortar made with waste concrete fines as a substitute for both binder and sand: Multi-properties evaluation

ANN, M5P-tree and nonlinear regression approaches with statistical evaluations to predict the compressive strength of cement-based mortar modified with fly ash

Soft computing techniques: Systematic multiscale models to predict the compressive strength of HVFA concrete based on mix proportions and curing times