光谱学与光谱分析, 2011, 31 (5): 1216, 网络出版: 2011-05-30
实验误差对近红外模型准确性的影响
The Influence of Reference Data Noise on the NIR Prediction Results
摘要
以相思树聚戊糖含量为例, 通过用不同精确度的数据建立的近红外模型预测性能, 讨论了不同精确度的数据对近红外模型准确性的影响。 结果表明, 建模原始数据的精确度在一定程度上影响着近红外模型的预测性能, 精确度越高, 建立的模型越好。 但对于精确度较小的的样品, 所建立的模型预测性能也能较好的预测未知样品。
Abstract
This article used hemicelluloses content in acacia spp. wood as a case study to demonstrate the influence of noise in the reference data on the results of NIR calibration model. The results indicated that the accuracy of NIR calibration model was affected by the reference data noise. The less noisy data was used in calibration model, the better result could be obtained. But when the noise was larger, NIR calibration model which was built by using regression mathematics methods can perform better than using primary reference data.
姚胜, 武国峰, 周舒珂, 姜亦飞, 金小娟, 赵强, 蒲俊文. 实验误差对近红外模型准确性的影响[J]. 光谱学与光谱分析, 2011, 31(5): 1216. YAO Sheng, WU Guo-feng, ZHOU Shu-ke, JIANG Yi-fei, JIN Xiao-juan, ZHAO Qiang, PU Jun-wen. The Influence of Reference Data Noise on the NIR Prediction Results[J]. Spectroscopy and Spectral Analysis, 2011, 31(5): 1216.