Machine learning-driven predictive modeling of mechanical properties in diverse steels
This study explores the application of machine learning (ML) in steel design using a small dataset of various steel grades that include 13 key elements and three critical mechanical properties. Random forest (RF) models were systematically evaluated for their robustness and effectiveness in predicti...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827025000179 |
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