A temperature prediction model for LF refined steel was established based on the XGBoost algorithm to address the issue of predicting the endpoint steel temperature in the LF process.In the offline testing stage of the temperature prediction model,the hit rates of the model were 79.8%and 98.5%respectively when the temperature error was±5℃and±10℃.After running the model online for a period of time,180 furnace data within a certain period were collected,and the hit rates of the model were 86.6%and 97.8%respectively when the temperature error was±5℃and±10℃.This temperature prediction model meets the actual usage needs of steel mills.
维普
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