Predicting the Mechanical Properties of RCA-Based Concrete Using Supervised Machine Learning Algorithms

• Published in: Materials Vol. 15; no. 2; p. 647
• Main Authors: Shang, Meijun, Li, Hejun, Ahmad, Ayaz, Ahmad, Waqas, Ostrowski, Krzysztof Adam, Aslam, Fahid, Joyklad, Panuwat, Majka, Tomasz M.
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.01.2022; MDPI
• Subjects: Accuracy; Aggregates; Algorithms; Classification; Compressive strength; Concrete; Construction materials; Correlation coefficients; Damage prevention; Data points; Decision trees; Environmental impact; Machine learning; Mechanical properties; Monte Carlo simulation; Natural resources; Recycled materials; Root-mean-square errors; Sensitivity analysis; Software; Statistical analysis; Superplasticizers; Tensile strength; Water absorption; compressive strength; concrete; fiber; mechanical properties; aggregate; split tensile strength

Environment-friendly concrete is gaining popularity these days because it consumes less energy and causes less damage to the environment. Rapid increases in the population and demand for construction throughout the world lead to a significant deterioration or reduction in natural resources. Meanwhil...