Paper Title:
BP Neural Network Fitting for Spectra of Blast Furnace Raceway
  Abstract

Three-layer BP neural network, particularly using Levenberg-Marquardt back-propagation with early stopping algorithm, is widely used in curve fitting, attributing to its fast speed and free from over-fitting. Hence, the trained network by Levenberg-Marquardt back-propagation was used for curve fitting of the radiation spectrum of blast furnace raceway. The results showed that Levenberg-Marquardt back-propagation with early stopping algorithm presented a better fitting ability. Additionally, the results of spectral fitting model showed that the blast furnace raceway had an effective radiation spectrum in the wavelength range from 420nm to 880nm, where the raceway could be considered as the gray body radiation.

  Info
Periodical
Edited by
Qi Luo
Pages
197-202
DOI
10.4028/www.scientific.net/AMM.55-57.197
Citation
B. Yang, N. Li, L. Lei, X. Wang, "BP Neural Network Fitting for Spectra of Blast Furnace Raceway", Applied Mechanics and Materials, Vols. 55-57, pp. 197-202, 2011
Online since
May 2011
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