Ontology highlight
ABSTRACT:
SUBMITTER: Lee JW
PROVIDER: S-EPMC7687896 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Lee Jin-Woong JW Park Woon Bae WB Do Lee Byung B Kim Seonghwan S Goo Nam Hoon NH Sohn Kee-Sun KS
Scientific reports 20201124 1
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 condition variables) is much higher than the output feature dimension (the number of material properties of concern). Rather than such a forward-prediction ML model, it is necessary to develop so-called inverse-d ...[more]