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。
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.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2011年第5期1216-1219,共4页
Spectroscopy and Spectral Analysis
基金
国家"十一五"科技支撑项目(2006BAD32B03)资助