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北京石油化工學院2026年研究生招生接收調(diào)劑公告

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星光小草

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[求助] 偏最小二乘法近紅外光譜

1、These methods with original and vector normalised spectra were used to develop calibration models。
2、The performance of the final PLS model was evaluated in terms of root mean square error of cross validation (RMSECV) for cross validation and root mean square error of prediction (RMSEP) during test validation, and the coefficient of determination (R2).
3、The residual (Res) is the difference between the true and fitted value. Thus the sum of squared errors (SSE) is the quadratic summation of these values ( Eq.1 ).
4、The root mean square error of estimation (RMSEE) is calculated from this sum, with “n” being the number of samples and “r” the rank ( Eq.2 ).
5、The determination coefficient, R2 ( Eq.3 ) gives the percentage of variance present in the true component values, which is reproduced in the regression.
6、R2 can be negative for low ranks, when the residual are larger than the variance in the true values (yi). In case of cross validation, the RMSECV is calculated using Eq.4 .
7、For the prediction set, the root mean square error of prediction (RMSEP) is calculated as follows ( Eq.5 ) [13].
8、The absorption peaks of NIR spectra were broad and overlap, making single wavelength calibration impossible due to large hidden information in spectral data.
9、 As a form of principal component analysis (PCA), PLS made use of the information of the NIR spectrum and the established analyte values as sociated with the spectrum.
10、It had no restriction in using the number of wavelengths that could be selected for the calibration to make the model suitable to extract the maximum information from the spectra.
11、The information extracted could be condensed in the latent variables or factors which were used in the calibration and prediction steps [12].

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1樓 2013-11-28 20:22:56

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【答案】應助回帖

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星光小草: 金幣+5, 翻譯EPI+1, ★★★很有幫助 2013-11-29 15:37:18

1、這些方法和原矢量歸一化光譜都被用于校正模型。
2、最后的PLS模型的性能評價主要在于根的交叉驗證均方誤差（RMSECV）的交叉驗證和根平均平方預測誤差（RMSEP）的試驗驗證和決定系數(shù)（R2）的測量。
3、殘余（RES）是真正的擬合值之間的差異。因此，誤差平方和（SSE）是這些值的平方的總和（1）。
4、均方根誤差估計（RMSEE）是按如下這個方法計算：“N”為樣本的數(shù)量和“R”的等級（水利）。
5、決定系數(shù)R2（式），給出了在真正的元件值存在差異的百分比，這是在回歸重現(xiàn)（不太清楚后半句意思）。
6、，當剩余大于真實值的方差（一），R2可以是負的低等級。在交叉驗證的情況下，預測計算Eq.4。

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2樓2013-11-29 08:51:18

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