A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns

•A novel approach is proposed to predict TBM’s position during construction.•The spatial and temporal relationships among the TBM parameters are considered.•A deep-learning framework that incorporates GCN and LSTM is established.•A realistic tunnel project in Singapore is used to demonstrate as a case study.•High prediction accuracy is achieved with average R2 of 0.941 for the deviations.