Predicting dynamic responses of frame structures subjected to stochastic wind loads using temporal surrogate model
Predicting dynamic responses of frame structures subjected to stochastic wind loads using temporal surrogate model
This study proposes an alternative approach based on the deep learning paradigm working in a complementary way with conventional methods such as the finite element method for quickly forecasting the responses of structures under random wind loads with reasonable accuracy. The approach works in a sequenceto-sequence fashion, providing a good trade-off between the prediction performance and required computation resources.