Airfoil Inverse Design Using a Deep Neural Net with an Explainable Attention Mechanism
Author:
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Aerospace Engineering,General Materials Science,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42405-023-00688-z.pdf
Reference29 articles.
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4. Dong Y (2018) An application of deep neural networks to the in-flight parameter identification for detection and characterization of aircraft icing. Aerosp Sci Technol 77:34–49
5. Hui X, Bai J, Wang H, Zhang Y (2020) Fast pressure distribution prediction of airfoils using deep learning. Aerosp Sci Technol 105:105949
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