云南化工2024，Vol.51Issue(4)：92-94,3.DOI:10.3969/j.issn.1004-275X.2024.04.21
不同产地葛根药材的高光谱结合人工神经网络鉴别
Hyperspectral Combined with Artificial Neural Network to Identify Pueraria Lobata Medicinal Materials from Different Origins
摘要
Abstract
The hyperspectral combined with artificial neural network(ANN)method was used to establish the identification method of Pueraria lobata from different origins.The hyperspectral data of six kinds of Pueraria lobata medicinal materials from different origins were collected,and the original spectral data were preprocessed by Savitzky-Golay smooth filtering,and the origin identification model of Pueraria lobata was es-tablished by artificial neural network method.The results show that compared with the accuracy of the unpreprocessed spectral data model,the classification accuracy of the ANN model established after Savitzky-Golay smoothing filtering reaches 99.00％.The results showed that hyper-spectral technology combined with artificial neural network could quickly and accurately identify the origin of Pueraria lobata,which was a promising method for identifying Pueraria lobata.关键词
葛根/高光谱/人工神经网络/产地鉴别Key words
Pueraria/Hyperspectral/Artificial Neural Networks/Origin Identification分类
化学化工引用本文复制引用
郭毅秦,焦龙,娄俊豪,沈瑞华,钟汉斌,熊迅宇..不同产地葛根药材的高光谱结合人工神经网络鉴别[J].云南化工,2024,51(4):92-94,3.基金项目
国家自然科学基金项目(No.211723003)、陕西省教育厅青年创新团队建设科研计划项目(No.21JP097、22JP064)、大学生创新创业训练计划项目(No.202210700010)、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(No.CQXA-2023-05)、西安石油大学科研创新团队(2019QNKYCXTD17)资助. （No.211723003）
