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Predictions for Unsteady Flow Fields With Deep Learning Models of LSTM and GRU

Deep learning methods based on time series prediction are widely applied to solving fluid dynamics problems. However, the application characteristics of Long Short-Term Memory (LSTM) and Gate Recurrent Unit (GRU) in fluid mechanics are lacking in the existing research. Therefore, this paper proposes...

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Principais autores: Zhang Xing-Wei, Chen Jian-Qiao, Zhang Ke, Zhang Shi-Xiong, He Hao-Xiang
Formato: Artigo
Idioma:Inglês
Publicado em: IEEE 2024-01-01
Colecção:IEEE Access
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Acesso em linha:https://ieeexplore.ieee.org/document/10704700/
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