A critical review on the application of machine learning in supporting auxetic metamaterial design
The progress of machine learning (ML) in the past years has opened up new opportunities to the design of auxetic metamaterials. However, successful implementation of ML algorithms remains challenging, particularly for complex problems such as domain performance prediction and inverse design. In this...
Збережено в:
| Автори: | , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IOP Publishing
2024-01-01
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| Серія: | JPhys Materials |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1088/2515-7639/ad33a4 |
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