Prediction model of calcination quality of lime shaft kiln based on tree regression
In order to improve the accuracy of automatic control of the production process of lime shaft kiln,Jianlong Xilin Iron and Steel Plant proposed to use tree regression to dynamically predict the CaO content of finished products.Aiming at the problem of many control parameters and complex coupling relationship,the correlation analysis method is used to optimize the parameters,so as to improve the reliability of the prediction of the random forest regression algorithm.Through the test of 9 characteristic parameter sample data,it is shown that the tree regression model can adapt well to the multi-factor and nonlinear industrial scene of gray stone calcination,and the accuracy of the prediction results meets the requirements of industrial control.
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