Modeling of CME and CIR driven geomagnetic storms by means of artificial neural networks

• Published in: Contributions to geophysics & geodesy Vol. 45; no. 1; pp. 53 - 65
• Main Authors: Revallo, Miloš, Valach, Fridrich, Hejda, Pavel, Bochníček, Josef
• Format: Journal Article
• Language: English
• Published: Bratislava De Gruyter Open 01.03.2015; Earth Science Institute, Slovak Academy of Sciences; Earth Science Institute, Slovak Academy of Sciences, Slovakia
• Subjects: Advanced Composition Explorer; Artificial neural networks; Computer simulation; Coronal mass ejection; coronal mass ejections (CMEs); Corotating Interaction Regions (CIR); corotating interaction regions (CIRs); Correlation analysis; Correlation coefficient; Correlation coefficients; DST Index; Geomagnetic storms; Geomagnetism; Libration; Magnetic storms; magnetosphere; Modelling; Neural networks; Satellites; Solar corona; Solar wind; Solar wind parameters; space weather; space weather, coronal mass ejections (cmes), corotating interaction regions (cirs), geomagnetic storms, magnetosphere, dst index; Storms; Wind measurement

A model of geomagnetic storms based on the method of artificial neural networks (ANN) combined with an analytical approach is presented in the paper. Two classes of geomagnetic storms, caused by coronal mass ejections (CMEs) and those caused by corotating interaction regions (CIRs), of medium and we...