R. D. Vladimirov, V. R. Shirokiy, O. G. Barinov, S. A. Dolenko, I. N. Myagkova
{"title":"Forecasting the State of the Earth’s Magnetosphere Using a Special Algorithm for Working with Multidimensional Time Series","authors":"R. D. Vladimirov, V. R. Shirokiy, O. G. Barinov, S. A. Dolenko, I. N. Myagkova","doi":"10.3103/S0027134924702266","DOIUrl":null,"url":null,"abstract":"<p>This study is devoted to the adaptation and application of a special multistage algorithm based on machine learning methods, developed for the analysis of multidimensional time series in solving problems of forecasting certain events and identifying their precursors—phenomena represented by an unknown combination of parameter values describing an object. In addition to forecasting events, the algorithm can be used to forecast the values of continuous quantities. In this study, we compare the results of application of this algorithm in forecasting of three physical quantities characterizing the state of the magnetosphere of the Earth—two geomagnetic indexes (Dst and Kp) and the flux of relativistic electrons (<span>\\(E>\\)</span> 2 MeV) in geostationary orbit.</p>","PeriodicalId":711,"journal":{"name":"Moscow University Physics Bulletin","volume":"79 2 supplement","pages":"S798 - S806"},"PeriodicalIF":0.4000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Moscow University Physics Bulletin","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.3103/S0027134924702266","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This study is devoted to the adaptation and application of a special multistage algorithm based on machine learning methods, developed for the analysis of multidimensional time series in solving problems of forecasting certain events and identifying their precursors—phenomena represented by an unknown combination of parameter values describing an object. In addition to forecasting events, the algorithm can be used to forecast the values of continuous quantities. In this study, we compare the results of application of this algorithm in forecasting of three physical quantities characterizing the state of the magnetosphere of the Earth—two geomagnetic indexes (Dst and Kp) and the flux of relativistic electrons (\(E>\) 2 MeV) in geostationary orbit.
期刊介绍:
Moscow University Physics Bulletin publishes original papers (reviews, articles, and brief communications) in the following fields of experimental and theoretical physics: theoretical and mathematical physics; physics of nuclei and elementary particles; radiophysics, electronics, acoustics; optics and spectroscopy; laser physics; condensed matter physics; chemical physics, physical kinetics, and plasma physics; biophysics and medical physics; astronomy, astrophysics, and cosmology; physics of the Earth’s, atmosphere, and hydrosphere.