Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques

• Published in: Materials Vol. 14; no. 22; p. 7034
• Main Authors: Xu, Yue, Ahmad, Waqas, Ahmad, Ayaz, Ostrowski, Krzysztof Adam, Dudek, Marta, Aslam, Fahid, Joyklad, Panuwat
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 19.11.2021; MDPI
• Subjects: Accuracy; Algorithms; Cement; Compressive strength; Concrete; Decision trees; Machine learning; Material properties; Mechanical properties; Parameter sensitivity; Performance evaluation; Performance prediction; Regression; Sensitivity analysis; Software; Statistical analysis; Support vector machines; Variables

The current trend in modern research revolves around novel techniques that can predict the characteristics of materials without consuming time, effort, and experimental costs. The adaptation of machine learning techniques to compute the various properties of materials is gaining more attention. This...