A machine learning approach for accelerated design of magnesium alloys. Part B: Regression and property prediction

A machine learning approach for accelerated design of magnesium alloys. Part B: Regression and property prediction

Machine learning (ML) models provide great opportunities to accelerate novel material development, offering a virtual alternative to laborious and resource-intensive empirical methods. In this work, the second of a two-part study, an ML approach is presented that offers accelerated digital design of...

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Bibliographic Details
Main Authors: M. Ghorbani, M. Boley, P.N.H. Nakashima, N. Birbilis
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-11-01
Series:Journal of Magnesium and Alloys
Subjects:
Magnesium alloys
Digital alloy design
Supervised machine learning
Regression models
Prediction performance
Online Access:http://www.sciencedirect.com/science/article/pii/S2213956723002165

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http://www.sciencedirect.com/science/article/pii/S2213956723002165

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