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What is ML-Based Strength Prediction for 3DCP about?

This study presents a novel approach for estimating the compressive strength (CS) of 3D printed fiber-reinforced concrete using eight machine learning algorithms and gene expression programming. The models were trained on a comprehensive dataset of over 299 mixtures, achieving high prediction accuracy, with R2 values ranging from 0.927 to 0.990. An empirical equation was developed based on the gene expression programming results, which can aid in optimizing concrete mixtures for practical applications in co

Author

seenightd

Language

EN