Abstract
This work deals with the first try to calculate the amount of Precipitable Water Vapor (PWV) in atmosphere by using machine learning and AI methods. We use the detector voltages series measured by radiometric system “MIAP-2” as the initial data for machine learning. The radiometer MIAP-2 works by “atmospheric dip method” in 2mm and 3mm atmospheric transparency windows. We also have PWV data series collected by Water Vapor Radiometer and GNSS receiver for data validation. The best convergence results were demonstrated by the independent component analysis (ICA) method with coefficient of determination R2= 0.53 and artificial neural network method (ANN) with R2= 0.8. These methods allow to reduce the systematic errors due to direct PWV calculation from raw radiometric data avoiding unnecessary steps opacity calculation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
