Machine learning and Big Data in deep underground engineering

Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree-support vector machine models

Development of an optimization model for a monitoring point in tunnel stress deduction using a machine learning algorithm

Laboratory evaluation of a low-cost micro electro-mechanical systems sensor for inclination and acceleration monitoring

Grouped machine learning methods for predicting rock mass parameters in a tunnel boring machine-driven tunnel based on fuzzy C-means clustering

ALSTNet: Autoencoder fused long-and short-term time-series network for the prediction of tunnel structure