基于嗅觉可视化技术的食用植物油分类识别Classification and recognition of edible vegetable oils based on olfactory visualization technology
为实现山茶油与3种常见食用植物油(菜籽油、大豆油和玉米油)的区分,制备可视化传感器阵列,采用嗅觉可视化技术对4种不同种类的食用植物油进行分类识别。采用主成分分析(PCA)对4种油样的特征数据进行降维,然后将降维后的数据导入K近邻(KNN)、极限学习机(ELM)、支持向量机(SVM) 3种分类模型中进行模型参数优化,对比了3种分类模型的分类结果。结果表明:建立的SVM分类模型性能最优,当输入主成分向量数为7、c=1.741 1、g=4.549 8时,SVM分类模型的测试集分类识别准确率为95.8%,五折交叉验证准确率为89.6%。制得的可视化传感器阵列可以实现4种食用植物油的分类识别,嗅觉可视化...
Main Author: | 杨干, 李大鹏,文韬,蒋涵,龚中良 YANG Gan, LI Dapeng, WEN Tao, JIANG Han, GONG Zhongliang |
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Format: | Article |
Language: | English |
Published: |
中粮工科(西安)国际工程有限公司
2023-11-01
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Series: | Zhongguo youzhi |
Subjects: | |
Online Access: | http://tg.chinaoils.cn/zgyz/ch/reader/create_pdf.aspx?file_no=20231117&flag=1 |
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