Interpretable machine learning excavates a low-alloyed magnesium alloy with strength-ductility synergy based on data augmentation and reconstruction

Interpretable machine learning excavates a low-alloyed magnesium alloy with strength-ductility synergy based on data augmentation and reconstruction

The application of machine learning in alloy design is increasingly widespread, yet traditional models still face challenges when dealing with limited datasets and complex nonlinear relationships. This work proposes an interpretable machine learning method based on data augmentation and reconstructi...

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Bibliographic Details
Main Authors: Qinghang Wang, Xu Qin, Shouxin Xia, Li Wang, Weiqi Wang, Weiying Huang, Yan Song, Weineng Tang, Daolun Chen
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-06-01
Series:Journal of Magnesium and Alloys
Subjects:
Magnesium alloy
Interpretable machine learning
Alloy design
Hetero-structure
Strength-ductility synergy
Online Access:http://www.sciencedirect.com/science/article/pii/S2213956725000192
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http://www.sciencedirect.com/science/article/pii/S2213956725000192

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