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Study on Detection Technology of Milk Powder Based on Support Vector Machines and Near Infrared Spectroscopy

机译:基于支持向量机和近红外光谱法的奶粉检测技术研究

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This paper presents a novel classifier to identify standard and sub-standard milk powder, which is built by support vector machines (SVM) and near infrared spectroscopy (NIR). The training set is composed of 38 samples and the testing set is composed of 12 samples. The correct classification ratio of the training set is up to 100%, while that of the testing set is up to 100%. The result indicates that the combination of SVM and NIR can be used as a fast, convenient, and safe technology to identify standard and sub-standard milk powder.
机译:本文介绍了一种新型分类器,用于识别标准和亚标准的奶粉,由支持向量机(SVM)和近红外光谱(NIR)构建。训练集由38个样本组成,测试集由12个样本组成。训练集的正确分类比率高达100%,而测试集的分类比率高达100%。结果表明,SVM和NIR的组合可用作快速,方便,安全的技术,以识别标准和亚标准奶粉。

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