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...

詳細記述

保存先:
書誌詳細
主要な著者: Yichuan Tang, Yuan Wan, Zhongqi Wang, Cong Zhang, Jiani Han, Chaohao Hu, Chengying Tang
フォーマット: Artigo
言語:Inglês
出版事項: Elsevier 2022-07-01
シリーズ:Materials & Design
主題:
Machine learning
Artificial neural networks
Amorphous alloy
Nanocrystalline alloys
Magnetic properties
オンライン･アクセス:http://www.sciencedirect.com/science/article/pii/S0264127522003483
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