Paper Title:
Spectra Modeling of Blast Furnace Raceway by Neural Network
  Abstract

Neural network with Levenberg-Marquardt back-propagation training is widely used in curve fitting, according to its fast speed and free from over-fitting. In order to solve the issue on local minimum that may be found in Levenberg-Marquardt back-propagation with early stopping, and to get optimum number of hidden neurons, the least mean test errors algorithm was used in repeatedly training the three-layer feed-forward network with variable structure. Furthermore, the trained network was used for curve fitting of the radiation spectrum of blast furnace raceway. The results on spectra modeling of blast furnace raceway showed that this algorithm presented a better fitting ability, characterized by the reservation of the details of the original spectra and better generalization ability.

  Info
Periodical
Edited by
Qi Luo
Pages
245-250
DOI
10.4028/www.scientific.net/AMM.55-57.245
Citation
B. Yang, N. Li, X. Wang, L. Lei, "Spectra Modeling of Blast Furnace Raceway by Neural Network", Applied Mechanics and Materials, Vols. 55-57, pp. 245-250, 2011
Online since
May 2011
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