Improved phase prediction of high-entropy alloys assisted by imbalance learning
Predicting phase formation is crucial in novel high-entropy alloys (HEAs) design. Herein, machine learning and imbalance learning algorithms were combined together to improve the phase prediction of HEAs. In this work, an extensive database by collecting experimental data from published literature w...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-10-01
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| Series: | Materials & Design |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127524006853 |
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