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用Shenk's方法提高芥酸NIR模型预测精度

DOI: 10.3969/j.issn.1000-1298.2007.8.070826, PP. 101-104

Keywords: Shenk's算法,光谱修正,校正模型

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Abstract:

在光谱测量的过程中,由于光谱仪器本身的精度和测量环境等因素,经常会出现光谱的漂移、线性或非线性改变。以基于近红外光谱分析建立菜籽油中芥酸预测模型为例,将多元校正Shenk's算法用于修正同台仪器测量的光谱差异,大大提高了校正模型的预测精度。结果表明,对于光谱修正后再建模预测,预测均方差从2.263下降到1.569,平均相对误差从4.6%下降到3.218%,相关系数也由0.780提高到了0.913,模型的预测精度显著提高。

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