Journal of Materials Informatics
All Journals
Search Log In
Home Articles Special Issues Volumes Webinars Videos
Journal of Materials Informatics
Search Submit
Home Articles Special Issues Volumes Webinars Videos

fig6

From:  Improved hardness prediction for reduced-activation high-entropy alloys by incorporating symbolic regression and domain adaptation on small datasets
Improved hardness prediction for reduced-activation high-entropy alloys by incorporating symbolic regression and domain adaptation on small datasets

Figure 6. The predicted vs. experimental values of samples from the testing set and the RAHEA dataset using (A) No-GPF trained model and (B) GPFOnly-trained model. RAHEA: Reduced-activation high-entropy alloy.

Journal of Materials Informatics
ISSN 2770-372X (Online)
Navigation
Follow Us
Navigation

Committee on Publication Ethics

https://members.publicationethics.org/members/journal-materials-informatics

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Committee on Publication Ethics

https://members.publicationethics.org/members/journal-materials-informatics

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/
Discover Content
Follow OAE
Twitter
Facebook
LinkedIn
YouTube
BiLiBiLi
WeChat
© 2016-2025 OAE Publishing Inc., except certain content provided by third parties