Predictions of Deep Excavation Responses Considering Model Uncertainty: Integrating BiLSTM Neural Networks with Bayesian Updating

Predictions of excavation responses frequently differ from monitoring data due to geotechnical uncertainties. This paper proposes an efficient Bayesian updating approach for excavation responses that considers the uncertainties of soil properties and the calculation model. To evaluate the depth-dependent characteristic of model uncertainty, the model factor is quantified by a constant part and a trending component. Bidirectional long short-term...