高光谱结合哈里斯鹰优化核极限学习机鉴别化橘红胎切片年份

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中文摘要：化橘红胎是药用历史悠久的广东省道地中药材,由于其制品收藏年份越久远价格越高,市面上常有以次充好的现象.为此,采用高光谱成像技术,结合哈里斯鹰优化核极限学习机对四组不同年份的化橘红胎切片样品进行鉴别.采集四个年份共193个化橘红胎切片样本400～1 000 nm的高光谱图像.首先采用主成分分析法(PCA)分析化橘红胎切片的原始反射光谱,然后分别采用Savitzky-Golay平滑(S-G平滑)、多元散射校正(MSC)、标准正态变量交换(SNV)对样本光谱进行预处理并建立核极限学习机(KELM)模型;发现经SNV处理的样本光谱的判别准确率最高,训练集达到99.24％,测试集95.56％;进一步用竞争性自适应重加权算法(CARS)、蒙特卡洛无信息变量消除法(MCUVE)对样本光谱进行特征波长的选择;最后,采用KELM建立判别模型,同时使用哈里斯鹰算法(HHO)优化KELM参数选择并比较建模效果.结果表明:基于HHO-KELM的判别效果相较KELM有0.76％～4.44％的提升,通过MCUVE筛选所得特征波段信息冗余明显减少且精度提升,训练集和测试集最佳准确率均可达100％,故采用高光谱成像技术可以实现对不同年份的化橘红胎切片进行无损鉴别.

外文标题：Identification of Citri Grandis Fructus Immaturus Based on Hyperspectral Combined With HHO-KELM

外文摘要：Citri grandis fructus immaturus is a local Chinese medicinal material with a long history of medicinal use in Guangdong Province,because the higher the price of the product with the older the production year,the phenomenon of shoddy charging is often in the market.The study used hyperspectral imaging technology combined with the Harris Eagle optimized(HHO)kernel extreme learning machine(KELM)to identify four sets of different years of citri grandis fructus immaturus.In this study,193 orange-red tire section samples were collected in four years,and hyperspectral images of 400～1 000 nm were collected.Firstly,the original reflection spectra of orange-red tire sections were analyzed by principal component analysis(PCA),and then Savitzky-Golay smoothing(S-G),multiple scattering correction(MSC),and standard normal variable exchange(SNV)were used to pretreat the sample spectra and establish KELM model,and found that the discrimination accuracy of the sample spectra treated by SNV was the highest,reaching 99.24％of the training set and 95.56％of the test set.Further,use of competitive adaptive weighting algorithm(CARS)and Monte Carlo Information-Free Variable Elimination(MCUVE)to select the characteristic wavelength of the sample spectrum;Finally,the discriminant model is established by KELM,and the HHO is used to optimize the KELM parameter selection and compare the modeling effect.The results show that the discrimination effect based on HHO-KELM is 0.76％～4.44％higher than that of KELM.The redundancy of feature band information obtained by MCUVE screening is significantly reduced,The accuracy is improved,and the optimal accuracy can reach 100％of the training set and 100％of the test set,so the use of hyperspectral imaging technology can realize the non-destructive identification of citri grandis fructus immaturus in different years.

外文关键词：

Citri grandis fructus immaturusHyperspectral imagingFeature selectionKernel extreme learning machine

作者：

谢百亨、马晋芳、周泳欣、韩雪勤、陈嘉泽、朱思祁、杨懋勋、黄富荣

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作者单位：

暨南大学光电工程系,广东广州 510632

广东医科大学药学院广东天然药物研究与开发重点实验室,广东东莞 523808

国家中药现代化工程技术研究中心海洋中药分中心,广东湛江 524023

关键词：

化橘红胎高光谱成像特征波长核极限学习机

基金：

国家自然科学基金广东省自然科学基金广州市科学技术攻关项目广东医科大学学科建设项目广东医科大学博士学位人员科研启动基金(2021)省科技专项(2021)

项目编号：

619750692018A03031310002021030000954SG21009GGDMUB20210212021A05199

出版年：

2024

DOI：

10.3964/j.issn.1000-0593(2024)05-1494-07

光谱学与光谱分析

中国光学学会

光谱学与光谱分析

CSTPCD北大核心

影响因子：0.897

ISSN：1000-0593

年,卷(期)：2024.44(5)