Near infrared spectrum online modeling method based on partial least square method
A partial least squares method and near-infrared spectroscopy technology, which is applied in the field of near-infrared spectroscopy detection, can solve the problems of reduced prediction accuracy and achieve the effect of improving computing efficiency
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[0044] Such as figure 2 As shown, taking the data collected by the near-infrared spectrometer in the 1350nm-1650nm band as an example:
[0045] a. Import the original spectrum: In this embodiment, the original spectral data is 340×51 matrix data, which contains 340 spectral data, each spectral data has 50 bands, and 1 calibration value data;
[0046]b. Preprocessing the original spectral data: In this embodiment, 10 preprocessing methods such as Gaussian smoothing, Gaussian derivation, and SG smoothing are used, and each preprocessing method is given a very wide range of parameter settings, with a total of 2000 A combination of preprocessing, the broad preprocessing combination is to increase the robustness of the online modeling model, thereby improving the prediction accuracy of the portable spectrometer;
[0047] c. Modeling by partial least squares method: set the search parameter interval of the modeling principal components to [1, 2, ..., 15], and extract the maximum v...
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