Neural network design for data-driven prediction of target geometry for an aerodynamic inverse design algorithm

With the current advancements in artificial intelligence and machine learning, data has become a powerful tool for major improvements in various fields. In the field of aerodynamic design, most algorithms utilize an iterative method to reach their target function or geometry due to their robustness....

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Veröffentlicht in:Journal of mechanical science and technology Jg. 38; H. 8; S. 3899 - 3919
Hauptverfasser: Shirvani, Ahmad, Nili-Ahmadabadi, Mahdi, Ha, Man Yeong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Seoul Korean Society of Mechanical Engineers 01.08.2024
Springer Nature B.V
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ISSN:1738-494X, 1976-3824
Online-Zugang:Volltext
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