Applications of Machine Learning in Mechanised Tunnel Construction: A Systematic Review

Tunnel Boring Machines (TBMs) have become prevalent in tunnel construction due to their high efficiency and reliability. The proliferation of data obtained from site investigations acquisition systems provides an opportunity for the application machine learning (ML) techniques. ML algorithms been successfully applied TBM tunnelling because they are particularly effective capturing complex, non-linear relationships. This study focuses on commonly used techniques tunnelling, with a particular emphasis processing, algorithms, optimisation techniques, evaluation metrics. primary concerns applications discussed, including predicting performance, surface settlement, time series forecasting. reviews current progress, identifies challenges, suggests future developments field intelligent construction. aims contribute ongoing efforts research industry toward improving safety, sustainability, cost-effectiveness underground excavation projects.