中国烟草学报2017，Vol.23Issue(2)：60-68,9.DOI:10.16472/j.chinatobacco.2015.498
基于NIR技术和ELM的烤烟烟叶自动分级
Automatic grading of flue-cured tobacco leaves based on NIR technology and extreme learning machine algorithm
摘要
Abstract
In order to minimize the influence of artificial experience on flue-cured tobacco leaf grading in purchasing process,a rapid grading method using near-infrared (NIR) spectroscopy combined with extreme learning machine (ELM) algorithm was proposed.A grouping method based on principle of similar quality and close price of flue-cured tobacco leaves was put forward.Cross validation was used to optimize the number of hidden nodes of ELM.The method was compared with commonly used multi-class classification algorithms,including K nearest neighbor (KNN),support vector machine (SVM),and random forest (RF) algorithm.Results showed that ELM classification model was superior to other methods with automatic optimization parameters,short training time,and high stability and predictability.The classification prediction accuracy of tobacco dataset A and B into high,medium,and low groups was 95.77％ and 94.23％,respectively.Furthermore,classification accuracy of subdividing high,medium,and low groups of tobacco prediction samples A was 85.71％,86.67％,and 100％,respectively,and subdivision accuracy of tobacco prediction samples B was 100％,92.86％ and 92.86％,respectively.Therefore,application of NIR technology combined with ELM could accurately determine flue-cured tobacco leaf grade,providing a promising tool for quality evaluation in flue-cured tobacco leaf purchasing process.关键词
烟叶分级/近红外光谱/极限学习机/分类模型/多分类算法Key words
tobacco grading/near-infrared spectroscopy/extreme learning machine/classification model/multi-class classification algorithm引用本文复制引用
宾俊,周冀衡,范伟,李鑫,梁逸曾,肖志新,李春顺..基于NIR技术和ELM的烤烟烟叶自动分级[J].中国烟草学报,2017,23(2):60-68,9.基金项目
国家自然科学基金资助项目(No.21275164),湖南省研究生科研创新资助项目(No.CX2015B237) （No.21275164）
