Machine learning approach for predicting tramp elements in the basic oxygen furnace based on the compiled steel scrap mix

Michael Schäfer, Ulrike Faltings, Björn Glaser

Open source

DOI: 10.1038/s41598-025-86406-z
Published: 2025-01-18
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-025-86406-z,
  title = {Machine learning approach for predicting tramp elements in the basic oxygen furnace based on the compiled steel scrap mix},
  author = {Michael Schäfer and Ulrike Faltings and Björn Glaser},
  year = {2025},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-025-86406-z},
  url = {https://doi.org/10.1038/s41598-025-86406-z}
}

RIS

TY  - JOUR
TI  - Machine learning approach for predicting tramp elements in the basic oxygen furnace based on the compiled steel scrap mix
AU  - Michael Schäfer
AU  - Ulrike Faltings
AU  - Björn Glaser
PY  - 2025
JO  - Scientific Reports
DO  - 10.1038/s41598-025-86406-z
UR  - https://doi.org/10.1038/s41598-025-86406-z
ER  -

APA

Schäfer, M., Faltings, U., & Glaser, B. (2025). Machine learning approach for predicting tramp elements in the basic oxygen furnace based on the compiled steel scrap mix. Scientific Reports. https://doi.org/10.1038/s41598-025-86406-z

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crossref · retrieved 2026-09-26T01:56:22.324Z