| 用人工神经网络处理谷物成分分析 |
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| 引用本文： | 严衍禄,吉海彦.用人工神经网络处理谷物成分分析[J].高等学校化学学报,1993,14(5):618-620. |
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| 作者姓名： | 严衍禄 吉海彦 |
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| 作者单位： | 北京农业大学生物学院，北京农业大学生物学院 北京 100094，北京 100094 |
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| 摘 要： | 本文用人工神经网络处理谷物的付立叶变换近红外漫反射光谱,对谷物中含量在10~(-1)～10~(-3)的蛋白质、脂肪和6种人体必需氨基酸定量分析数据进行了解析,分析结果与经典化学方法没有系统偏差,且优于逐步回归分析法的结果。
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| 关 键 词： | 人工神经网络 定量分析 谷物化学 |
The Quantitative Analysis for Cereal s Components by Artificial Neural Networks |
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| JI Hai-Yan,YAN Yan-Lu.The Quantitative Analysis for Cereal s Components by Artificial Neural Networks[J].Chemical Research In Chinese Universities,1993,14(5):618-620. |
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| Authors: | JI Hai-Yan YAN Yan-Lu |
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| Abstract: | Cereal' s eight components (the concentration between 10-1~ 10-3), that is , protein (Pro), fat(Fat), leucine(Leu), isoleucine(Ile), valine(Val), threonine(Thr), phenylalanine(Phe) and lysine(Lys) were quantitatively analyzed by Artificial Neural Networks. For the eight components the prediction correlation coefficients (R) are 0.969, 0.892, 0.897, 0.884, 0.970, 0,860, 0. 854, 0. 899, and the coefficients of variability are 2. 66% , 5, 39% , 7. 62% , 7. 06%, 2. 97% , 7, 83%, 13. 38%, 2. 68% respectively. These results are superior to those of SRA, and have no systematical errors with classical chemistry' s methods. |
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| Keywords: | Artificial neural networks Quantitative analysis Cereal |
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