Truncated Newton Kernel Ridge Regression for Prediction of Porosity in Additive Manufactured SS316L
Despite the many benefits of additive manufacturing, the final quality of the fabricated parts remains a barrier to the wide adoption of this technique in industry. Predicting the quality of parts using advanced machine learning techniques may improve the repeatability of results and make additive m...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
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MDPI AG
2022-04-01
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| Schriftenreihe: | Applied Sciences |
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| Online-Zugang: | https://www.mdpi.com/2076-3417/12/9/4252 |
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