Dynamic feature capturing in a fluid flow reduced-order model using attention-augmented autoencoders

This study looks into how adding adaptive attention to convolutional autoencoders can help reconstruct flow fields in fluid dynamics applications. The study compares the effectiveness of the proposed adaptive attention mechanism with the convolutional block attention module approach using two differ...

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Vydané v:	Engineering applications of artificial intelligence Ročník 149; s. 110463
Hlavní autori:	Beiki, Alireza, Kamali, Reza
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.06.2025
Predmet:	Adaptive attention mechanisms Convolutional autoencoders Flow field reconstruction Reduced-order modeling Time series forecasting in fluid dynamics Convolutional autoencoders Reduced-order modeling Flow field reconstruction Time series forecasting in fluid dynamics Adaptive attention mechanisms
ISSN:	0952-1976
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