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- Title
Forecasting Ice Jams on the Lena River Using Machine Learning Methods.
- Authors
Malygin, I. V.; Aleshin, I. M.
- Abstract
The application of a predictive intellectual system previously developed for the Northern Dvina River is considered for a new region—the basin of the Lena River. The use of this technology under conditions of another region becomes possible due to the similar formulation of the problem of forecasting and publishing new open sets of hydrological and meteorological data for the period of 1985–2019. Based on the results of observations at gauging and meteorological stations, the system makes it possible to form a short-term forecast of the formation of powerful ice jams in river sections under conditions of incompleteness and data gaps. Interpolation methods based on machine learning are used to prepare the initial data and eliminate gaps. Calculations have shown the efficiency of the predictive system. The estimated accuracy of forecasting is 76%. The assessment of the importance of the factors have shown the common influence of groups of factors in different regions on the final result of the ice jamming process.
- Subjects
MACHINE learning; METEOROLOGICAL observations; ICE on rivers, lakes, etc.; METEOROLOGICAL stations; INTERPOLATION; FORECASTING
- Publication
Izvestiya, Atmospheric & Oceanic Physics, 2022, Vol 58, Issue 10, p1218
- ISSN
0001-4338
- Publication type
Article
- DOI
10.1134/S0001433822100061