期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2014
卷号：11
期号：3
出版社：IJCSI Press
摘要：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.
关键词：RBF neural network£¬the multiple linear model£¬ Natural language
