Prediction Model of Leaf Structures of Tobacco Strips Based on the Appearance Features of Tobacco Leaves and Threshing Techni-cal Parameters
[Objective]To explore the relationship between appearance features of tobacco leaves,threshing technical parameters and leaf structure of tobacco strips,to provide theoretical basis for improving the quality of the threshing and redrying process.[Method]Taking the leaf structure prediction model as the research object,870 tobacco leaf appearance features,threshing technical parameters and corresponding leaf structure data were selected as the training set,and machine learning regression models were constructed including support vector machine,ran-dom forest,multi-layer perceptron.Model selection was based on the cross-validation MAE of the training set.The generalisation performance of the selected regression models was evaluated using 97 tobacco appearance features,threshing technical parameters and corresponding leaf struc-ture data as the test set.[Result]The best model for predicting the percentage of strips with>25.4 mm was SVR,with relative percentage difference and goodness of fit of 1.685 8 and 0.648 1 on the test set,respectively,and the correlation coefficient between the predicted values and the true values of 0.806 2.The best model for predicting the percentage of strips of 12.7-25.4 mm was Random Forest,with relative per-centage difference and goodness of fit of 1.590 8 and 0.604 9 on the test set,respectively,and the correlation coefficient between the predicted and true values was 0.780 4.[Conclusion]Based on the appearance features of tobacco leaves and the threshing technical parameters,the SVR and Random Forest models were constructed and appropriate hyperparameters were selected,which could accurately predict the the percentage of strips with>25.4 mm and the percentage of strips of 12.7-25.4 mm.
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