Supervised Machine Learning Models for Predicting SS304H Welding Properties Using TIG, Autogenous TIG, and A-TIG
This investigation explores the application of supervised machine learning regression approaches to predict various responses, including penetration, bead width, bead height, hardness, ultimate tensile strength, and percentage elongation in autogenous TIG-, A-TIG-, and TIG-welded joints of SS304H, w...
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| 主要な著者: | , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI AG
2025-06-01
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| シリーズ: | Crystals |
| 主題: | |
| オンライン･アクセス: | https://www.mdpi.com/2073-4352/15/6/529 |
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