Concentration Measuring Device and Method Based on Spectra Learning

Abstract: there is disclosed a method for generating a concentration prediction model for predicting a concentration of a target substance through machine learning. the method includes a training data generation step of generating an optimal transformed spectrum obtained by transforming a basic spectrum of a substance of a known concentration according to a predetermined transformation condition as training data, and a concentration prediction model generation step of generating a concentration prediction model by machine learning the optimal transformed spectrum generated in the training data generation step and transformed according to the predetermined transformation condition and an actually measured concentration of a substance corresponding to the optimal transformed spectrum, and the method may improve accuracy in substance concentration prediction by suppressing a spectral change caused by compounds other than an analyte to be predicted and maximizing the spectral change with a concentration of the analyte.

Inventor(s): Jae Hyun Kim, Byung Mook Kim, Jin Yeong Lee, Kyu Hwang Lee, Young Soo Song

CPC Classification: G01N21/31 (INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing processes other than immunoassay, involving enzymes or microorganisms , ))

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