Dirty engineering data-driven inverse prediction machine learning model
Abstract Most data-driven machine learning (ML) approaches established in metallurgy research fields are focused on a build-up of reliable quantitative models that predict a material property from a given set of material conditions. In general, the input feature dimension (the number of material con...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2020
|
| Subjects: | |
| Online Access: | https://doaj.org/article/97f45af18b5640c5a76a5470b7e82b31 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|