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Predicting dynamic responses of frame structures subjected to stochastic wind loads using temporal surrogate model

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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.
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Predicting dynamic responses of frame structures subjected to stochastic wind loads using temporal surrogate model