为解决近红外光谱分析中的模型传递问题，本研究提出了一元线性回归直接标准化算法( Simple linear regression direct standardization，SLRDS)。为验证算法的有效性，采用玉米样品的近红外光谱集进行实验，并与传统的直接标准化算法( Direct standardization， DS)、分段直接标准化算法( Piecewise direct standardi-zation， PDS)进行比较。实验结果表明，SLRDS算法不仅能够有效消除近红外光谱仪之间的差异，很好地实现玉米样品的PLS校正模型在3台仪器之间的共享，而且与DS和PDS算法相比，具有传递性能高、模型简单及所求参数少等优点。
Near Infrared Spectroscopic Model Transfer Based on Simple Linear Regression
To solve the calibration transmission problem in near-infrared ( NIR) spectroscopy, a novel model transfer method, Simple Linear Regression Direct Standard-ization ( SLRDS ) , has been presented. To investigate the validity of the proposed method, a real corn sample NIR dataset was tested and the direct standardization ( DS ) method and piecewise direct standardization ( PDS ) method were involved as a comparison. Our results indicated that SLRDS can correct compressed NIR data differences among instruments and enable the user to share corn sample PLS calibration model among three instruments, at the same time it has higher prediction accuracy, fewer parameters and simpler model than DS and PDS.
Near-infrared spectroscopyModel transferSimple linear regression
国家科技期刊平台
NSTL
万方数据
维普
