Prediction of TBM jamming risk in squeezing grounds using Bayesian and artificial neural networks
This study presents an application of artificial neural network (ANN) and Bayesian network (BN) for evaluation of jamming risk of the shielded tunnel boring machines (TBMs) in adverse ground conditions such as squeezing grounds.The analysis is based on database of tunneling cases by numerical modeling to evaluate the ground convergence and possibil