The Converter Steelmaking End Point Prediction Model Based on RBF Neural Network

Xian Liang Dong; Shi Dong

doi:10.4028/www.scientific.net/AMM.577.98

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 577The Converter Steelmaking End Point Prediction...

The Converter Steelmaking End Point Prediction Model Based on RBF Neural Network

Abstract:

The mathematical model of convert steelmaking end point prediction model based on RBF(Radical Basis Function) is presented in this paper. According to the end point prediction problem of the converter steelmaking production prediction problem, we establish the forecast model of converter steelmaking process which describes the relationship between variables such as hot metal quality, oxygen blowing, the quality of the cooling agent and additives etc. and the end point molten steel temperature and carbon content. The prediction system is multidimensional and nonlinear. The model between variables and the target is unknown. For this situation, this paper applies RBF neural network to forecast target, establishing the prediction model based on RBF neural network. So as to obtain the variables and the mathematical model between steel endpoint temperature and carbon content.

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Periodical:

Applied Mechanics and Materials (Volume 577)

Pages:

98-101

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.577.98

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Online since:

July 2014

Authors:

Xian Liang Dong*, Shi Dong

Keywords:

Converter Steelmaking, End-Point Prediction, Gaussian Function, RBF Neural Network

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* - Corresponding Author

References

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