Application of machine learning in predicting the rate-dependent compressive strength of rocks

• Main Authors: Wei, Mingdong, Meng, Wenzhao, Dai, Feng, Wu, Wei
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Civil engineering; Machine Learning; Rock Dynamics
• Online Access: https://hdl.handle.net/10356/160259
• Institution: Nanyang Technological University

Accurate prediction of compressive strength of rocks relies on the rate-dependent behaviors of rocks, and correlation among the geometrical, physical, and mechanical properties of rocks. However, these properties may not be easy to control in laboratory experiments, particularly in dynamic compressi...