Construction and application of the classification model for cigarette blend raw material based on thermal analysis spectrum
[Background]This study aims to improve the work efficiency of classification and grading of cigarette blend raw materials,and help formula personnel to objectively grasp the annual fluctuation of formula raw materials.[Methods]A new technique is proposed for classifying and grading cigarette blend raw materials by combining thermal analysis spectra with the Support Vector Machine(SVM)algorithm.The SVM module in sklearn of python3 is used,and through the kernel function and one-against-all method and selecting appropriate penalty parameters,129 samples from the years 2016-2018 are trained,and 33 samples are tested.After determining the prediction accuracy of the model,the model was applied to the classification evaluation of 46 samples in 2019.[Results]The classification accuracy rate of the 129 training set samples was 93.02%,the classification accuracy rate of the 33 test set samples was 84.85%,and the classification accuracy rate of the 46 cigarette blend raw materials was 84.78%.
cigarette blend raw materialclassificationthermal analysis spectrumsupport vector machine
万方数据
维普
