光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2014年
5期
1429-1433
,共5页
稳定竞争自适应重加权采样%无标样%模型传递%波长筛选%光谱分析
穩定競爭自適應重加權採樣%無標樣%模型傳遞%波長篩選%光譜分析
은정경쟁자괄응중가권채양%무표양%모형전체%파장사선%광보분석
Stability competitive adaptive reweighted sampling%Without standard samples%Calibration transfer%Wavelength se-lection%Spectral analysis
提出了一种基于稳定竞争自适应重加权采样（stability competitive adaptive reweighted sampling ， SCARS）的无标模型传递方法。利用有用信息标准即稳定度指数（定义为回归系数除以其标准偏差的绝对值）和传递后的预测均方根误差（root mean squared error of prediction ，RMSEP），选择重要的、受测样参数影响不敏感的波长变量，能够消除或减少不同仪器或测量条件对样本信息反应差异，提高模型传递效果。此外，在该方法中，光谱变量被压缩、降维，从而使模型传递更稳定。采用该方法对谷物的近红外光谱分析模型在不同仪器之间进行传递研究。结果表明，该方法能消除仪器间的大部分差异，较好地实现模型传递效果。与正交信号校正法（orthogonal signal correction ，OSC）、蒙特卡罗结合无用信息变量消除法（Monte Carlo unin-formative variable elimination ，MCUVE）、竞争自适应重加权采样法（competitive adaptive reweighted sam-pling ，CARS）的比较表明，SCARS不仅在传递精度上能取得比OSC、MCUVE及CARS更好的效果，而且能有效地对光谱数据进行压缩，简化并优化传递过程。
提齣瞭一種基于穩定競爭自適應重加權採樣（stability competitive adaptive reweighted sampling ， SCARS）的無標模型傳遞方法。利用有用信息標準即穩定度指數（定義為迴歸繫數除以其標準偏差的絕對值）和傳遞後的預測均方根誤差（root mean squared error of prediction ，RMSEP），選擇重要的、受測樣參數影響不敏感的波長變量，能夠消除或減少不同儀器或測量條件對樣本信息反應差異，提高模型傳遞效果。此外，在該方法中，光譜變量被壓縮、降維，從而使模型傳遞更穩定。採用該方法對穀物的近紅外光譜分析模型在不同儀器之間進行傳遞研究。結果錶明，該方法能消除儀器間的大部分差異，較好地實現模型傳遞效果。與正交信號校正法（orthogonal signal correction ，OSC）、矇特卡囉結閤無用信息變量消除法（Monte Carlo unin-formative variable elimination ，MCUVE）、競爭自適應重加權採樣法（competitive adaptive reweighted sam-pling ，CARS）的比較錶明，SCARS不僅在傳遞精度上能取得比OSC、MCUVE及CARS更好的效果，而且能有效地對光譜數據進行壓縮，簡化併優化傳遞過程。
제출료일충기우은정경쟁자괄응중가권채양（stability competitive adaptive reweighted sampling ， SCARS）적무표모형전체방법。이용유용신식표준즉은정도지수（정의위회귀계수제이기표준편차적절대치）화전체후적예측균방근오차（root mean squared error of prediction ，RMSEP），선택중요적、수측양삼수영향불민감적파장변량，능구소제혹감소불동의기혹측량조건대양본신식반응차이，제고모형전체효과。차외，재해방법중，광보변량피압축、강유，종이사모형전체경은정。채용해방법대곡물적근홍외광보분석모형재불동의기지간진행전체연구。결과표명，해방법능소제의기간적대부분차이，교호지실현모형전체효과。여정교신호교정법（orthogonal signal correction ，OSC）、몽특잡라결합무용신식변량소제법（Monte Carlo unin-formative variable elimination ，MCUVE）、경쟁자괄응중가권채양법（competitive adaptive reweighted sam-pling ，CARS）적비교표명，SCARS불부재전체정도상능취득비OSC、MCUVE급CARS경호적효과，이차능유효지대광보수거진행압축，간화병우화전체과정。
A novel calibration transfer method based on stability competitive adaptive reweighted sampling (SCARS) was pro-posed in the present paper .An informative criterion ,i .e .the stability index ,defined as the absolute value of regression coeffi-cient divided by its standard deviation was used .And the root mean squared error of prediction (RMSEP) after transfer was also used .The wavelength variables which were important and insensitive to influence of measurement parameters were selected . And then the differences in responses of different instruments or measurement conditions for a specific sample were eliminated or reduced to improve the calibration transfer results .Moreover ,in the proposed method ,the spectral variables were compressed , making calibration transfer more stable .The application of the proposed method to calibration transfer of NIR analysis was eval-uated by analyzing the corn with different NIR spectrometers .The results showed that this method can well correct the differ-ence between instruments and improve the analytical accuracy .The transfer results obtained by the proposed method ,orthogonal signal correction (OSC) ,Monte Carlo uninformative variable elimination (MCUVE) and competitive adaptive reweighted sam-pling (CARS) ,respectively ,for corn with different NIR spectrometers indicated that the former gave the best analytical accura-cy ,and was effective for the spectroscopic data compression which can simplify and optimize the transfer process .
