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Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
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| Published in: | Journal of Mechanical Engineering and Sciences |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1867301673975676930 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Journal of Mechanical Engineering and Sciences |
| description | |
| discipline_display | Mechanical Engineering |
| discipline_facet | Mechanical Engineering |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:62572 |
| institution | FRELIP |
| journal_source_facet | Journal of Mechanical Engineering and Sciences |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools Mechanical Engineering General Mechanical Engineering |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Mechanical Engineering General Mechanical Engineering Mechanical Engineering General Mechanical Engineering |
| subject_facet | Mechanical Engineering General Mechanical Engineering |
| title | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_auth | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_full | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_fullStr | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_full_unstemmed | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_short | Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools |
| title_sort | hybrid approaches for sheet metal formability prediction: a synergy of experimental, numerical and machine learning tools |
| topic | Mechanical Engineering General Mechanical Engineering |
| url | https://journal.ump.edu.my/index.php/jmes/article/view/12371 |