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Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132435/ https://www.ncbi.nlm.nih.gov/pubmed/37213791 http://dx.doi.org/10.1007/s00466-023-02337-4 |
| _version_ | 1785031387108081664 |
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| author | Liu, Wing Kam Bessa, Miguel A. Chinesta, Francisco Li, Shaofan Trask, Nathaniel |
| author_facet | Liu, Wing Kam Bessa, Miguel A. Chinesta, Francisco Li, Shaofan Trask, Nathaniel |
| author_sort | Liu, Wing Kam |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-10132435 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2023 |
| publisher | Springer Berlin Heidelberg |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-101324352023-04-27 Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization Liu, Wing Kam Bessa, Miguel A. Chinesta, Francisco Li, Shaofan Trask, Nathaniel Comput Mech Editorial Springer Berlin Heidelberg 2023-04-26 2023 /pmc/articles/PMC10132435/ /pubmed/37213791 http://dx.doi.org/10.1007/s00466-023-02337-4 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
| spellingShingle | Editorial Liu, Wing Kam Bessa, Miguel A. Chinesta, Francisco Li, Shaofan Trask, Nathaniel Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title | Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title_full | Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title_fullStr | Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title_full_unstemmed | Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title_short | Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| title_sort | special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimization |
| topic | Editorial |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132435/ https://www.ncbi.nlm.nih.gov/pubmed/37213791 http://dx.doi.org/10.1007/s00466-023-02337-4 |
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