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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2020-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-020-77575-0 |