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OALib Journal期刊
ISSN: 2333-9721
费用：99美元
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近红外光谱法最小二乘双胞胎支持向量机的应用研究
DOI: 10.3724/SP.J.1096.2012.11054, PP. 950-954
Keywords: 最小二乘双胞胎支持向量机,近红外光谱,化学计量学,大黄
Abstract:
依据中药大黄的近红外光谱信息,采用最小二乘双胞胎支持向量机(LSTSVM)算法,通过MATLAB软件编程,建立参数可优化识别模型,实现了对中药大黄的真伪鉴别。将实验材料98个大黄样品随机划分为训练集和测试集,对于训练集60个样品采用留1/5法交叉验证优化模型参数,以所选最优化参数结合训练集样品的近红外光谱建立最优识别模型,对测试集的38个样品的真伪进行识别,识别率可达97.4%。结果表明,LSTSVM算法是一种有效的识别方法,可依据中药大黄的近红外光谱对其真伪进行快速识别。同时,本研究将大黄样品6次随机划分为训练集和测试集,建模预测平均识别率为93.4%,表明采用LSTSVM算法建立识别模型具有较好的稳健性。
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