高光谱结合支持向量机鉴别不同产地的麦冬药材
Discrimination of Ophiopogon Japonicus from Different Origions by Hyperspectroscopy Combined with Support Vector Machine
陈碧佳 1焦龙 1李红 1钟汉斌 1娄俊豪 1沈瑞华1
作者信息
- 1. 西安石油大学 化学化工学院,陕西 西安 710065
- 折叠
摘要
采用高光谱结合支持向量机方法建立了不同产地麦冬药材的鉴别方法.收集5个不同产地的麦冬样品并采集其高光谱数据,用SG平滑滤波对高光谱数据预处理,再结合支持向量机方法建立麦冬产地分类模型.结果显示,经预处理后模型对测试集的分类准确率可达到93.00％.结果表明,高光谱结合支持向量机方法是一种很有前景的麦冬药材鉴别方法.
Abstract
The identification method of Ophiopogon japonicus from different origions was established by hyperspectroscopy combined with support vector machine.The hyperspectral datas of Ophiopogon japonicus samples from five different origions were collected,and the hyperspectral datas were preprocessed by Savitzky-Golay smooth derivative,and then the classification model of Ophiopogon japonicus origions was established by combined with support vector machine.The results show that the classification accuracy of the model after pretreatment can reach 93.00％.The research shows that hyperspectral technique combined with support vector machine was a promising method for the identification of Ophiopogon japonicus.
关键词
高光谱/支持向量机/麦冬/产地鉴别Key words
Hyperspectrum/Support Vector Machine/Ophiopogon Japonicus/Region Identification引用本文复制引用
基金项目
国家自然科学基金(22373075)
陕西省教育厅青年创新团队建设科研计划(21JP097)
陕西省教育厅青年创新团队建设科研计划(22JP064)
川庆钻探公司-西安石油大学致密油气藏勘探开发研究中心科技项目(CQXA-2023-05)
西安石油大学科研创新团队(2019QNKYCXTD17)
出版年
2024
国家科技期刊平台
NSTL
万方数据