Machine learning models for predicting the compressive strength of sustainable recycled aggregate concrete incorporating supplementary cementitious materials

Key Points

• Compressive strength predictions are critical for assessing material performance, particularly in sustainable construction.
• The study utilizes robust machine learning models that enhance prediction accuracy for concrete incorporating recycled materials.
• Various supplementary cementitious materials are evaluated, showcasing their effects on the compressive strength of concrete structures.
• Findings suggest significant implications for future construction practices and environmental sustainability through recycled aggregates.