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Artificial Neural Network Predictive System for Oxygen Steelmaking Converter

  • Jan Falkus
  • Piotr Pietrzkiewicz
  • Wojciech Pietrzyk
  • Jan Kusiak
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)

Abstract

The main objective of the paper is the presentation of the static control model of steelmaking converter process based on the artificial neural network approach. The results of classical mass and energy balance as well as regression models are also presented. The developed artificial neural network predicts the temperature of the liquid metal and the volume of necessary oxygen blow. The ANN was trained and tested with the real industrial data measured in one of the Polish steel plants. The comparison of the ANN results with the classical calculations is presented.

Keywords

Artificial Neural Network Liquid Metal Energy Balance Model Metal Bath Converter Lining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jan Falkus
    • 1
  • Piotr Pietrzkiewicz
    • 1
  • Wojciech Pietrzyk
    • 1
  • Jan Kusiak
    • 1
  1. 1.Akademia Górniczo-HutniczaKrakówPoland

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