Open AccessApplication of Machine Learning in Cigarette Quality Evaluation Method
Author(s) -
Jingju Lin,
Haolin Guo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1607/1/012011
Subject(s) - computer science , quality (philosophy) , machine learning , artificial intelligence , artificial neural network , evaluation methods , support vector machine , preference , data mining , reliability engineering , mathematics , statistics , engineering , philosophy , epistemology
In the evaluation of cigarette quality, it usually depends on the sense organs of evaluation experts. But due to the influence of many subjective and objective factors, the accuracy of evaluation results is often difficult to guarantee. Therefore, this paper proposes a method of cigarette quality evaluation based on SVM and BP neural network. The experimental results show that the method can establish a nonlinear mapping relationship between the measured values of cigarette chemical components and the evaluation values of expert quality, and reflect the preference information and reasoning mechanism of evaluation experts. So the model is an objective and reliable method for evaluating the internal quality of tobacco after knowing the chemical composition test data of tobacco.