Adversarially trained LSTMs on reduced order models of urban air pollution simulations
This paper presents an approach to improve computational fluid dynamics simulations forecasts of air pollution using deep learning. Our method, which integrates Principal Components Analysis (PCA) and adversarial training, is a way to improve the forecast skill of reduced order models obtained from the original model solution... (read more)
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Sigmoid Activation
PCA
Tanh Activation
Memory Network
LSTM