Building a Model for Time Reduction of Steel Scrap Meltdown in the Electric Arc Furnace (EAF): General Strategy with a Comparison of Feature Selection Methods

  • Tadeusz Wieczorek
  • Marcin Blachnik
  • Krystian Ma̧czka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5097)


Time reduction of steel scraps meltdown during the electic arc process is really a challenging problem. Typically the EAF process is stochastic without any determinism and only simple and naive rules are currently used to manage such processes. The goal of the paper is to present the way, which have been considered, to build an accurate model concerning different feature selection methods that would be helpful in predicting the end of the meltdown and maximum energy needed by the furnace.


Support Vector Machine Feature Selection Mean Square Error Mutual Information Feature Subset 
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 2008

Authors and Affiliations

  • Tadeusz Wieczorek
    • 1
  • Marcin Blachnik
    • 1
    • 2
  • Krystian Ma̧czka
    • 1
  1. 1.Electrotechnology DepartmentSilesian University of TechnologyPoland
  2. 2.Adaptive Informatics Research CentreHelsinki University of TechnologyEspooFinland

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