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Research on the Alkalinity of Sintering Process Based on LS-SVM Algorithms

  • Rui Wang
  • Ai-min Wang
  • Qiang Song
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 168)

Abstract

The measurement of R in sintering process is difficult to control, on the other hand, it is easily to be disturbed by almost process steps. A prediction model of R in sintering process based on LS-SVM is proposed to judge the trend of R. The application result shows that the prediction with this method can achieve higher robust, better utility and expensive value. It was concluded that the LS-SVM model is effective with the advantages of high precision, less requirement of samples and comparatively simple calculation.

Keywords

Alkalinity of sinter LS-SVM Prediction The sintering process 

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References

  1. 1.
    Fan, X.-H., Wang, H.-D.: Mathematical model and Artificial Intelligence of sintering process. Central South University Press (2002)Google Scholar
  2. 2.
    Song, Q., Wang, A.-M.: Simulation and Prediction of Alkalinity in Sintering Process Based on Grey Least Squares Support Vector Machine. Journal of Iron and Steel Research, International 16(5), 1–6 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Rui Wang
    • 1
  • Ai-min Wang
    • 2
  • Qiang Song
    • 3
  1. 1.Mechanical and Electrical EngineeringXinxiang UniversityXinxiangChina
  2. 2.Computer Science DepartmentAnyang Normal UniversityAnyangChina
  3. 3.Mechanical Engineering DepartmentAnyang Institute of TechnologyAnyangChina

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