Ján Kaˇ cur, Patrik Flegner
The basic oxygen steelmaking process (BOS) faces the issue of the absence of information about the melt temperature and the carbon concentration in the melt. Although deterministic models for predicting steelmaking process variables are being developed in metallurgical research, machine-learning models can model the nonlinearities of process variables and provide a good estimate of the target process variables. In this paper, five machine learning methods were applied to predict the temperature and carbon concentration in the melt.
@article{fddedac8-a2ec-48bf-a200-a9c8d59773fc,
title={047 Prediction of Temperature and Carbon Concentration in Oxygen Steelmaking by Machine Learning A Comparative Study},
author={Ján Kaˇ cur and Patrik Flegner},
year={2026},
language={en}
}TY - JOUR TI - 047 Prediction of Temperature and Carbon Concentration in Oxygen Steelmaking by Machine Learning A Comparative Study AU - Ján Kaˇ cur AU - Patrik Flegner PY - 2026 LA - en ER -
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