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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Yichuan Tang, Yuan Wan, Zhongqi Wang, Cong Zhang, Jiani Han, Chaohao Hu, Chengying Tang
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2022-07-01
Schriftenreihe:Materials & Design
Schlagworte:
Machine learning
Artificial neural networks
Amorphous alloy
Nanocrystalline alloys
Magnetic properties
Online Zugang:http://www.sciencedirect.com/science/article/pii/S0264127522003483
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge