Abstract
A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. The goal of the paper is to present the way to predict temperature of melted steel in the electric arc furnace and consequently, to reduce the number of temperature measurements during the process. Reducing the number of temperature measurements shortens the time of the whole process and allows increasing production.
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Blachnik, M., Mączka, K., Wieczorek, T. (2010). A Model for Temperature Prediction of Melted Steel in the Electric Arc Furnace (EAF). In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_45
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DOI: https://doi.org/10.1007/978-3-642-13232-2_45
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