Matrix data processing method and device and storage medium

Abstract

The embodiment of the invention discloses a matrix data processing method and device and a storage medium. The method comprises the following steps: determining a first training matrix from a first spectrum matrix associated with a host, and determining a second training matrix from a second spectrum matrix associated with a slave; performing data preprocessing on the first training matrix and thesecond training matrix to obtain a first processing matrix and a second processing matrix; performing fixed half-window expansion on the second processing matrix to obtain a first expansion matrix, and performing feature reconstruction on the first expansion matrix to obtain a first feature matrix; training an initial regression model according to the first processing matrix and the first featurematrix to obtain a target regression model carrying a transfer coefficient matrix F; and obtaining a third spectral matrix associated with the slave, and predicting to obtain a target spectral matrixassociated with the host according to the third spectral matrix and the target regression model. By adopting the embodiment of the invention, the cross-equipment transfer capability of the sample canbe improved.

Description

technical field

[0001] The present application relates to the technical field of near-infrared spectral analysis, and in particular to a method, device and storage medium for matrix data processing. Background technique

[0002] With the continuous improvement of people's living standards, people's requirements for fruit quality are also getting higher and higher. Quality inspection and grading of post-harvest fruits have become an essential part of standardized fruit processing. Due to the advantages of fast, non-destructive, and online detection and analysis, near-infrared spectroscopy is widely used in the detection of fruit sugar content.

[0003] At present, the industry usually uses the standard normal transformation algorithm to preprocess the collected near-infrared spectral data to eliminate the influence of solid particle size, surface scattering and optical path changes on the diffuse scattering spectrum of near-infrared light. However, the deviation standard cau...

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