Spectra Modeling of Blast Furnace Raceway by Neural Network

Bo Yang; Ning Li; Xue Wang; Liang Lei

doi:10.4028/www.scientific.net/AMM.55-57.245

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 55-57Spectra Modeling of Blast Furnace Raceway by...

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.

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Periodical:

Applied Mechanics and Materials (Volumes 55-57)

Pages:

245-250

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.55-57.245

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Online since:

May 2011

Authors:

Bo Yang, Ning Li, Xue Wang, Liang Lei

Keywords:

Least Mean Test Error, Neural Network (NN), Raceway, Spectra Fitting

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