End-point Temperature Prediction Based on Rbf Neural Network
نویسندگان
چکیده
An end-point temperature prediction model based on RBF neural network is developed to reduce the measuring cost and improve the measuring accuracy in a vacuum induction furnace. It can give reliable predictions of tapping time and temperature of molten steel in the first-round prediction. And the prediction accuracy can be improved by the error correction in the secondround prediction. 120 set of data are used for model building and validation.The experimental results show that the proposed method is effective and the real-world application is potential. Copyright c © 2005 IFAC
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تاریخ انتشار 2005