CAJ | 학술논문

采用全谱建立多元校正模型时,通常计算鼍大,模型不够稳健,而且模型的预测精度往往也不能达到最优.文章介绍一种新的波长选择方法:采用连续投影算法(successive projiections algorithin),并将其集成偏最小二乘(partial least squares)多变量校正技术构成SPA-PLS方法,用于谷物小麦近红外光谱波长优化选择及其与水分含量的定量分析.结果表明:在经SPA算法后,光谱波数可削减97.72%,后继的定量校正模型结构得到显著简化,模型的稳健性也大大增强;同时,被选取的波长物理意义明确,模型的解释能力增强,而模型的预测性能也与GA-PLS方法相当.
채용전보건립다원교정모형시,통상계산타대,모형불구은건,이차모형적예측정도왕왕야불능체도최우.문장개소일충신적파장선택방법:채용련속투영산법(successive projiections algorithin),병장기집성편최소이승(partial least squares)다변량교정기술구성SPA-PLS방법,용우곡물소맥근홍외광보파장우화선택급기여수분함량적정량분석.결과표명:재경SPA산법후,광보파수가삭감97.72%,후계적정량교정모형결구득도현저간화,모형적은건성야대대증강;동시,피선취적파장물리의의명학,모형적해석능력증강,이모형적예측성능야여GA-PLS방법상당.
Successive projections algorithm combined with partial least squares regression, termed as SPA-PLS approach, was implemented as a novel variable selection approach to multivariate calibration. The proposed approach was applied to near-infra-red reflectance data for analyzing moisture in wheat. The number of variables selected from 701 spectral variables was reduced to 16 by SPA, and the root mean squared error of prediction set (RMSEP) of the corresponding partial least squares regression models was decreased to 0. 205 5% as well The result indicates that the SPA-PLS approach by performing SPA prior to calibra-tion not only can improve the model accuracy, but also decreases the number of spectral variables, so its resulting model becomes more concise. Moreover, as compared with genetic algorithm for wavelength selection, SPA is a deterministic search technique whose results are reproducible and it is more robust with respect to the choice of the validation set.