Prediction model for indoor rock compression failure time based on ensemble learning and optimization algorithms

Bayesian-Optimized Machine Learning Framework with SHAP Interpretation for Rockburst Intensity Prediction in Deep Underground Engineering

As mineral resource development moves deeper into the earth, mine dynamic disasters, represented by rockbursts, occur frequently. Due to the combined effects of in situ rock stress state and geostress conditions, it is difficult to obtain reliable prediction results using traditional empirical criteria or single-index...

Machine Learning Prediction of the Ground Reaction Curve in Sand with the MATLAB GUI Platform

The proposed framework combined a curated database, neural network-based curve prediction, and hyperparameter optimization, providing a robust approach for evaluating the soil arching effect, providing a robust approach for evaluating the soil arching effect.

Machine Learning-Based Compressive Strength Prediction and Multi-Objective Optimization of Ultra-High Performance Concrete

The compressive strength of ultra-high-performance concrete (UHPC) is jointly influenced by multiple factors, including material composition, mixture proportion parameters, and curing regime. Conventional empirical methods are therefore insufficient to accurately characterize the highly nonlinear relationships involved...

Tree Based Machine Learning Framework for Stability Evaluation of Square Tunnels in Sloping Rock

The proposed AFELA–machine learning framework provides a computationally efficient, reliable, and interpretable approach for tunnel stability assessment in sloping rock mass conditions.

Hybrid data-driven model for predicting the peak shear strength of rock joints

Prediction and Generalization Capability of Machine Learning Models for Shield TBM-Induced Settlement

Ground settlement induced by shield tunnel boring machine (TBM) excavation is a major geotechnical concern in urban tunneling because it may affect the safety of adjacent structures and underground infrastructure. In this study, machine learning models were developed to predict the maximum settlement induced by shield...