烟草科技2019，Vol.52Issue(2)：101-108,8.
基于GA-SVM算法的烤烟香型自动识别研究
Automatic recognition of flavor types of flue-cured tobacco based on GA-SVM algorithm
摘要
Abstract
In order to recognize the characteristic difference of flue-cured tobacco of different flavor types, 514 samples of flue-cured tobacco of fresh, robust and medium flavor types were collected, and 68 aroma components in tobacco samples were determined. By adopting data analysis and pattern recognition technology, an automatic recognition method for tobacco flavor type was proposed on the basis of tobacco aroma components and genetic algorithm-support vector machine (GA-SVM) algorithm. Genetic algorithm was used to optimize and adjust the parameters of support vector machine, and a 5-fold cross-validation method was used to calculate the classification accuracy of the proposed method. The classification results of GA-SVM, SVM and naive Bayesian algorithms were compared, the results showed that the flavor type discrimination accuracies of the three algorithms for the samples were 96.40%, 78.58% and 84.42%, respectively; GA-SVM was significantly more accurate than the other two algorithms. The proposed method provides a technical support for the accurate flavor type discrimination and growing area tracing of flue-cured tobacco.关键词
烤烟/香型/致香成分/遗传算法/支持向量机/自动识别Key words
Flue-cured tobacco/Flavor type/Aroma component/Genetic algorithm/Support vector machine/Automatic recognition分类
轻工纺织引用本文复制引用
邱昌桂,孔兰芬,杨式华,杨双艳,刘静,张建强,袁天军,刘泽..基于GA-SVM算法的烤烟香型自动识别研究[J].烟草科技,2019,52(2):101-108,8.基金项目
云南瑞升烟草技术(集团)有限公司项目"烟叶品质数字化评价技术的平台建设研究"(RS2014010). （集团）
