Enhancing ship hydrodynamic performance via machine learning-driven CFD parametric optimization
In order to improve the efficiency of ship hydrodynamic optimization and reduce resistance, this study employed machine learning methods to predict resistance. In response to the limitations of machine learning's generalization ability on high-dimensional sparse data, an IXGB-MAML hybrid model based...
Tallennettuna:
| Päätekijät: | , , , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Taylor & Francis Group
2025-12-01
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| Sarja: | Engineering Applications of Computational Fluid Mechanics |
| Aiheet: | |
| Linkit: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2565801 |
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