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当前位置: 首页 > 文章 > 基于可见/近红外光谱谱区有效波长的梨品种鉴别 农业机械学报 2013,44 (3) 153-157+179
Position: Home > Articles > Variety Identification of Pears Based on Effective Wavelengths in Visible/Near Infrared Region Transactions of the Chinese Society for Agricultural Machinery 2013,44 (3) 153-157+179

基于可见/近红外光谱谱区有效波长的梨品种鉴别

作  者：
李江波;赵春江;陈立平;黄文倩
单  位：
北京农业智能装备技术研究中心
关键词：
梨;品种鉴别;可见/近红外光谱;有效波长;最小二乘支持向量机
摘  要：
基于最小二乘支持向量机(LS-SVM)建模方法,提出应用梨在可见/近红外光谱谱区的有效波长(EW)进行其品种鉴别的新方法。用210个样本作为建模定标集,30个样本进行预测。根据偏最小二乘法分析载荷图和回归系数图选择鉴别梨品种的有效波长,并建立EW与最小二乘支持向量机相结合的EW-LS-SVM模型,同时与应用逆反馈人工神经网络(BP-ANN)建立的EW-BP-ANN模型进行判别准确率的比较。结果表明,应用LS-SVM和BP-ANN建立的模型对建模样本和预测集样本的判别准确率分别为100%和93.3%。研究表明,应用EW-LS-SVM模型进行梨品种鉴别是可行的。
译  名：
Variety Identification of Pears Based on Effective Wavelengths in Visible/Near Infrared Region
作  者：
Li Jiangbo Zhao Chunjiang Chen Liping Huang Wenqian(Beijing Research Center of Intelligent Equipment for Agriculture,Beijing 100097,China)
关键词：
Pears Variety identification Visible/near infrared spectra Effective wavelengths Least squares-support vector machine
摘  要：
Based on least squares-support vector machine(LS-SVM),the effective wavelength(EW) in visible/near infrared(Vis/NIR) region was proposed as a new approach for the variety discrimination of pears.210 pear samples were used for the calibration set,while 30 samples for the validation set.After partial least squares(PLS) analysis,the EWs were selected according to the X-loading weights and regression coefficients,and an EW-LS-SVM model was developed for the variety discrimination.This model was compared with EW-BP-ANN model by using back-propagation artificial neural network(BP-ANN).Results showed that the same recognition accuracies(100% for the calibration set,93.3% for the validation set) were obtained for EW-LS-SVM and EW-BP-ANN models,respectively.Studies show that it is feasible to use EW-LS-SVM model for the variety discrimination of pears.

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