Prediction of TBM jamming risk in squeezing grounds using Bayesian and artificial neural networks

• 作 者: Rohola Hasanpour Jamal Rostami
• 机 构: InstituteforTunnelingandConstructionManagement,DepartmentofMiningEngineering,DepartmentofCivilEngine
• 出 处: 岩石力学与岩土工程学报:英文版
• 发表日期: 2020年1期
• 关键词: BAYESIAN network(BN) Artificial neural network(ANN) Shielded tunnel BORING machi

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