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Ironmaking & Steelmaking
Processes, Products and Applications
Volume 37, 2010 - Issue 6
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Articles

Prediction and control for silicon content in pig iron of blast furnace by integrating artificial neural network with genetic algorithm

W. ChenCollege of Metallurgy and Energy Engineering, Hebei Polytechnics University, Tangshan063009, China;, Email: [email protected]
,
B.-X. WangTangshan Heavy Plate CO. LTD, Tangshan063604, China
&
H.-L. HanCollege of Metallurgy and Energy Engineering, Hebei Polytechnics University, Tangshan063009, China
Pages 458-463 | Published online: 18 Jul 2013

References

  • J. Chen: Eng. Appl. Artif. Intell., 2001, 14, 77–85.
  • W. Chen, B.-X. Wang, Z.-S. Tong and X.-R. Zhang: J. HeBei Inst. Technol., 2005, 27, (4), 15–17.
  • B. Yao, T.-J Yang and X.-J. Ning: J. Univ. Sci. Technol. Beijing, 2000, 4, (7), 55–58.
  • J. S. Son, D. M. Lee, I. S. Kim and S. K. Choi: J. Mater. Process. Technol., 2004, 153–154, 643–648.
  • H.-L. Han and X.-L. Yan: J. HeBei Inst. Technol., 2006, 28, (2), 23–27.
  • W. Wang: ‘The principle of artificial neural network’, 10–31; 1995, Beijing, Beihang University Press.
  • M.-Q. Li: ‘The principle and application of genetic algorithm’, 2–105; 2002, Beijing, Science Press.
  • N. K. Nath and K. Mitra: Ironmaking Steelmaking, 2004, 31, 199–206.

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