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NI-拉曼光谱结合BP-Adaboost神经网络用于茶油中大豆油掺假检测
Journal of Food Measurement and Characterization ( IF 2.9 ) Pub Date : 2022-05-18 , DOI: 10.1007/s11694-022-01430-1 Junhao Kuang , Ningning Luo , Zhongqi Hao , Jinjun Xu , Xingdao He , Jiulin Shi
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更新日期:2022-05-18
Journal of Food Measurement and Characterization ( IF 2.9 ) Pub Date : 2022-05-18 , DOI: 10.1007/s11694-022-01430-1 Junhao Kuang , Ningning Luo , Zhongqi Hao , Jinjun Xu , Xingdao He , Jiulin Shi
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为提高茶油掺假的准确性,首次开发了一种利用近红外拉曼光谱结合BP-Adaboost神经网络(BP-ANN)模型的实时快速检测方法。采用主成分分析对纯山茶油、大豆油、山茶油掺大豆油的拉曼光谱数据进行降维。使用 Adaboost 算法优化反向传播神经网络模型,以区分正品和掺假山茶油。成功建立了用于检测茶油掺假的BP-ANN模型。该模型得到的预测线性值大于0.999,均方误差小于1%。
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