An active machine learning approach for optimal design of magnesium alloys using Bayesian optimisation

Abstract In the pursuit of magnesium (Mg) alloys with targeted mechanical properties, a multi-objective Bayesian optimisation workflow is presented to enable optimal Mg-alloy design. A probabilistic Gaussian process regressor model was trained through an active learning loop, while balancing the exp...

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Главные авторы:	M. Ghorbani, M. Boley, P. N. H. Nakashima, N. Birbilis
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Nature Portfolio 2024-04-01
Серии:	Scientific Reports
Предметы:	Mg alloys Alloy design Machine learning Bayesian optimisation Sequential design strategy
Online-ссылка:	https://doi.org/10.1038/s41598-024-59100-9
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