![]() One-dimensional convolutional neural network (1D-CNN) and long-short term memory (LSTM) network are adopted for seismic responses modeling of a two-story and three-span subway station in a data-driven fashion as opposed to the computational expensive physics-based finite element model. The proposed method takes the deformation of the free field where the subway station is located as the input to predict seismic responses of the subway station according to the characteristic of seismic responses of underground structures. ![]() A novel and computationally inexpensive method for predicting the nonlinear seismic response of subway stations using deep learning approaches is developed to reduce the computational cost in stochastic seismic responses analysis.
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June 2023
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