Analysis of the Results of Astroclimate Measurements in the Millimeter Wavelength Range Using Machine Learning Methods
Authors:
- 1 June 2024
- journal article
- research article
- Published by Pleiades Publishing Ltd in Astrophysical Bulletin
- Vol. 79 (2) , 340-349
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.Keywords
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