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...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Yichuan Tang, Yuan Wan, Zhongqi Wang, Cong Zhang, Jiani Han, Chaohao Hu, Chengying Tang
Format: Artigo
Langue:Inglês
Publié: Elsevier 2022-07-01
Collection:Materials & Design
Sujets:
Machine learning
Artificial neural networks
Amorphous alloy
Nanocrystalline alloys
Magnetic properties
Accès en ligne:http://www.sciencedirect.com/science/article/pii/S0264127522003483
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires