Method for establishing multiple models of near infrared spectrums

Abstract

The invention provides a method for establishing multiple models of near infrared spectrums. The method comprises the steps that collected near infrared spectrums and corresponding detected constituent concentration data are divided into a training set and a prediction set; a boosting method is used for sampling the training set again, at the very start, the same sampling weight is given to all wavelength points, and a certain number of wavelength points are selected to establish a PLS submodel; a prediction spectrum is obtained through the product of the score and the load of the PLS submodel; an index loss function of the difference value of the prediction spectrum and a modeling subset spectrum is used for giving weights to all wavelength points of a training subset; when the wavelength points are selected in the next time, and the larger the weight is, the larger the sampling probability of a sample is; the above steps are executed repeatedly, and a plurality of submodels are established; the weighted average of the prediction results of the models are used as the prediction concentrated value of a sample of the prediction set. According to the method, the submodels are established in the wavelength direction, the boosting method is used for conducting training continuously to establish the multiple models at last, the prediction precision for quantitative analyzing the models is improved, and a novel quantitative analyzing method is provided for multivariate calibration analyzing of the near infrared spectrums.

Description

technical field [0001] The invention of the method belongs to the non-destructive analysis technology in the field of analytical chemistry, and in particular relates to a near-infrared spectrum modeling method. Background technique [0002] Quantitative analysis of complex samples has always been a challenging problem in the field of analytical chemistry and industrial production. Complex samples generally have complex matrices and various components. Traditional analysis methods are difficult to apply to the quantitative analysis of complex sample components. It is urgent to develop new and rapid quantitative analysis techniques. Near-infrared spectroscopy is a non-destructive analysis technique. It stands out among many analysis methods due to its fast analysis speed, simple sample pretreatment, and good stability. It is widely used in agriculture, petrochemicals, medicine, food and other fields. However, due to the serious overlap of near-infrared spectral bands, weak si...

AI Technical Summary

Problems solved by technology

The boosting method is a multi-model modeling method with excellent performance, among which the boosting multi-model modeling based on sample resampling has achieved good results, but when the number of samples is small, it is difficult to resample the samples, so , it is necessary to further develop the boosting multi-model modeling method based on wavelength resampling to solve the prediction accuracy of the model especially when the number of samples is small

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