Machine learning and Python assisted design and verification of Fe–based amorphous/nanocrystalline alloy

We report a machine learning (ML) and Python assisted strategy to accelerate the design and verification of Fe–based amorphous and nanocrystalline alloy with desired properties. Linear Regression (LR), Support Vector Regression (SVR), Decision Tree Regression (DTR), Artificial Neural Network (ANN) a...

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Библиографические подробности
Главные авторы: Yichuan Tang, Yuan Wan, Zhongqi Wang, Cong Zhang, Jiani Han, Chaohao Hu, Chengying Tang
Формат: Artigo
Язык:Inglês
Опубликовано: Elsevier 2022-07-01
Серии:Materials & Design
Предметы:
Machine learning
Artificial neural networks
Amorphous alloy
Nanocrystalline alloys
Magnetic properties
Online-ссылка:http://www.sciencedirect.com/science/article/pii/S0264127522003483
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