Prediction of rock mass classification in tunnel boring machine tunneling using the principal component analysis (PCA)–gated recurrent unit (GRU) neural network

Ke Man a,b, Liwen Wu a, Xiaoli Liu c, Zhifei Song a, Kena Li a, Nawnit Kumar c
a College of Civil Engineering, North China University of Technology, Beijing, China
b Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization, Shenzhen University, Shenzhen, China
c State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China

Due to the complexity of underground engineering geology, the tunnel boring machine (TBM) usually shows poor adaptability to the surrounding rock mass, leading to machine jamming and geological hazards. More read:
https://onlinelibrary.wiley.com/doi/full/10.1002/dug2.12084