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A numerical study of fish adaption behaviors in complex environments with a deep reinforcement learning and immersed boundary–lattice Boltzmann method
Fish adaption behaviors in complex environments are of great importance in improving the performance of underwater vehicles. This work presents a numerical study of the adaption behaviors of self-propelled fish in complex environments by developing a numerical framework of deep learning and immersed...
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| Publicat a: | Sci Rep |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Publishing Group UK
2021
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7814145/ https://ncbi.nlm.nih.gov/pubmed/33462281 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-81124-8 |
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