Prediction and Research of Temperature and Humidity at the Outlet of Super Return Based on Random Forest Algorithm

In order to explore the relationship between the process parameters of the super return section of the silk production line and the outlet temperature and moisture, and improve the process quality, the 2022 hard shell Yuxi formula tobacco leaf was used as the raw material. Temperature and moisture, and improve the process quality, the 2022 hard shell Yuxi formula tobacco leaf was used as the raw material. Based on Pearson correlation coefficient, the linear correlation between the super return section thin sheet flow rate, circulating air temperature, hot air temperature, steam flow rate, circulating air humidity, steam flow rate zone 1, steam flow rate zone 2, and the outlet temperature and moisture was analyzed, Then, according to the OOB estimation method of the Random forest algorithm, the importance of the six characteristic parameters is evaluated Then, according to the OOB estimation method of the Random forest algorithm, the importance of the six characteristic parameters is evaluated, and a Random forest prediction model is established to predict the outlet temperature and moisture of the super return section. Goodness of fit of the model is 84.3%, 71.3%, and the fitting effect is good, which can provide a certain reference value for in-depth research on the super return section of the silk production process.