Study on Productive Process Model Basic Oxygen Furnace Steelmaking Based on RBF Neural Network
The endpoint temperature and carbon content of basic oxygen furnace (BOF) are the control of the BOF steelmaking process. There exists a complex relationship among them and each control variable. While the multiple linear model is limited to predict the endpoint temperature and carbon content through each control variable, and the online continue measurement cant be made. So the predictive model of some control variables of the BOF steelmaking based on RBF neural network was put forward, and the study of verifying model was made by comparing the predictive value with the practical data of 89 converters in a factory. It turned out that the method has high accurate prediction, and it can be used in the process of prediction in steel enterprises.
Keywords: RBF neural network£¬the multiple linear model£¬ Natural language
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ABOUT THE AUTHOR
Zhihong Ma
Zhi-hong Ma (1975-), male, born in Ningxia, Associate Professor of the Tianjin agricultural University, master's degree, mainly engaged in the teaching of mathematics and applied mathematics research.
Zhihong Ma
Zhi-hong Ma (1975-), male, born in Ningxia, Associate Professor of the Tianjin agricultural University, master's degree, mainly engaged in the teaching of mathematics and applied mathematics research.
