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Short- and Medium-range Prediction of Relativistic Electron Flux in the Earth’s Outer Radiation Belt by Machine Learning Methodsстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 23 сентября 2021 г.
- Авторы: Myagkova I.N., Shirokii V.R., Shugai Yu S., Barinov O.G., Vladimirov R.D., Dolenko S.A.
- Журнал: Russian Meteorology and Hydrology
- Том: 46
- Номер: 3
- Год издания: 2021
- Издательство: Allerton Press Inc.
- Местоположение издательства: United States
- Первая страница: 163
- Последняя страница: 171
- DOI: 10.3103/s1068373921030043
- Аннотация: The ways are studied to improve the quality of prediction of the time series of hourly mean fluxes and daily total fluxes (fluences) of relativistic electrons in the outer radiation belt of the Earth 1 to 24 hours ahead and 1 to 4 days ahead, respectively. The prediction uses an approximation approach based on various machine learning methods, namely, artificial neural networks (ANNs), decision tree (random forest), and gradient boosting. A comparison of the skill scores of short-range forecasts with the lead time of 1 to 24 hours showed that the best results were demonstrated by ANNs. For medium-range forecasting, the accuracy of prediction of the fluences of relativistic electrons in the Earth’s outer radiation belt three to four days ahead increases significantly when the predicted values of the solar wind velocity near the Earth obtained from the UV images of the Sun of the AIA (Atmospheric Imaging Assembly) instrument of the SDO (Solar Dynamics Observatory) are included to the list of the input parameters.
- Добавил в систему: Мягкова Ирина Николаевна