Spectral model transmission method based on unary linear regression
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A linear regression and model transfer technology, applied in the field of spectral analysis, can solve problems such as too many parameters and insufficient accuracy of the transfer model
Active Publication Date: 2014-10-08
GUILIN UNIV OF ELECTRONIC TECH
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[0007] In short, the existing spectral model transfer method requires more parameters, and the accuracy of the transfer model is not high enough
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Embodiment 1
[0051] The method flow of this example is as follows figure 1 As shown, the main steps are as follows:
[0052] Ⅰ. Pretreatment of sample spectra
[0053] In this example, there are 3 near-infrared spectroscopic analysis instruments, which are recorded as A, B, and C respectively. The 4 main components of 80 corn samples are known: the reference values of water, oil, protein and starch content. The sample set contains the near-infrared spectra of 80 corn samples measured on three different spectrometers, and the spectral wavelength range is 1100-2498nm with an interval of 2nm. In this example, the spectral data collected on three spectroscopic instruments are smoothed and preprocessed with the Savitzky-Golay smoothing method, the window size is 17, and the polynomial order is 3.
[0054] Ⅱ. Establishment of Calibration Model
[0055] In this example, firstly, the 80 corn samples were sorted according to the reference values of the contents of the four components; then, ...
Embodiment 2
[0108] The process of this example is also as figure 1 shown.
[0109] Ⅰ. Pretreatment of sample spectra
[0110] In this example, there are 2 spectrometers, denoted as D and E respectively. The sample set in this example contains 88 gasoline samples, and 88 near-infrared spectrum samples are measured on two spectrometers, and the spectral collection range is 700-1100nm. At the same time, the reference values of C7, C8, C9 and C10 component contents in each sample are known.
[0111] In this example, the standardized method is used to preprocess the spectral data collected on two spectrometers.
[0112] Ⅱ. Establishment of Calibration Model
[0113] In this example, the 88 gasoline samples are firstly sorted according to the reference values of the contents of the four components in gradients; then each of the 30 samples is selected as the prediction set, and the remaining 58 samples are used as the calibration set. The sample has 4 components, so there are 4 calibrat...
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Abstract
The invention discloses a spectral model transmission method based on unary linear regression. The spectral model transmission method mainly comprises the steps of I. performing the identical preprocessing on sample spectrums of M spectrometers; II. classifying spectrum data into m correction sets and forecasting sets according to m kinds of components of samples, and respectively constructing m correction models on the M spectrometers; III. evaluating the correction models; IV. selecting the spectrometer with the best forecasting effect as a main instruments and the other spectrometers as auxiliary instruments; and V. selecting optimal samples for all the auxiliary instruments from a correction set of the main instrument, determining samples in conversion sets of all the auxiliary instruments according to the sequence numbers, calculating regression coefficients through the unary linear regression, correcting spectrums of the auxiliary instruments, and substituting the regression coefficients into the correction model of the main instrument to obtain a sample component content result. According to the method, the difference of the different instruments is effectively eliminated; the correction model constructed on the main instrument can be shared on the multiple auxiliary instruments; the analysis test workload is reduced, and the cost of the model construction is saved; furthermore, the number of calculated parameters is small, the models are simple, and the forecasting accuracy is relatively high.
Description
technical field [0001] The invention belongs to the technical field of spectral analysis, in particular to a spectral model transfer method based on unary linear regression. Background technique [0002] Spectral analysis technology is a comprehensive analysis technology developed on the basis of spectral detection, chemometrics, computer science and application testing, and now it has received more and more attention. At the same time, spectral analysis technology has become one of the research hotspots in the field of chemical analysis due to its unique advantages. The quantitative application in spectral analysis technology depends on the calibration model, that is, to correlate the reference value (component content or physical and chemical properties) of the standard sample set with the corresponding spectrum, establish the functional relationship between the two, and apply the spectrum to the unknown sample. The quantitative calibration model calculates predicted valu...
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