Analysis of the Results of Astroclimate Measurements in the Millimeter Wavelength Range Using Machine Learning Methods
摘要
Abstract
This paper presents a method for estimating precipitable water vapor from radiometric data using machine learning methods. The results of a study of precipitated water vapor for the territory of Chirag (Dagestan), Terskol peak (Elbrus region), Badary observatory (Buryatia) and the Spitsbergen archipelago are presented. A comparative analysis of the assessment of precipitable water vapor for the territory of ‘‘Badary’’ was carried out using GNSS, MERRA-2, water vapor radiometer data and predicting values using machine learning methods based on data from the MIAP-2 microwave radiometer.