Predicting shear strength of quartzite using portable index tests: a machine learning approach
Jinhao Dai
Shear strength of rock, characterized by the internal friction angle (φ) and cohesion (c), is the basis for the design and stability evaluation of foundation, rock slope and underground excavation. Obtaining φ and c through traditional methods such as laboratory or on-site tests is usually time-consuming and costly. This study adopts three algorithm-optimized machine learning models: Particle Swarm optimized (PSO) Support Vector Machine (SVM), Dung Beetle optimized (DBO) Random Forest (RF) and A