Abstract
The results of prediction of geomagnetic indexes characterizing the state of the Earth's magnetosphere obtained with the help of artificial neural networks (ANN) for various prediction horizons are presented. The forecasts are based on multivariate time series including the values of the geomagnetic indices themselves, as well as data about the parameters of solar wind and interplanetary magnetic field, during several latest hours.
Highlights
The Earth’s magnetosphere is one of the key space environment domains affected by solar wind (SW)
Experimental studies show that geomagnetic storms have a significant impact on the nearEarth radiation environment, because after them the flux of the relativistic electrons of Outer Radiation Belt of the Earth usually increases for an order of magnitude or more (e.g. [2,3] and references therein)
To assess and compare the quality of models, the following statistical indexes characterizing the deviation of the prediction from the real values of the predicted quantities were used in this study: the multiple determination coefficient R2 (R squared), the root mean squared error (RMSE), the correlation coefficient(r)
Summary
The Earth’s magnetosphere is one of the key space environment domains affected by solar wind (SW). Index of magnetic activity derived from the network of nearequatorial geomagnetic observatories that measures the intensity of the globally symmetrical equatorial electrojet (the "ring current") It has been calculated at the World Data Center WDCC2 at Kyoto, Japan (Geomagnetic Equatorial Dst index Home Page, http://wdc.kugi.kyoto u.ac.jp/dstdir/index.html) since the International Geophysical Year, 1957, using data from four observatories at low to midlatitudes; its hourly values are available online. The Swedish Space Weather Centre (http://src.irf.se/en/forecasts/) predicts the hourly value of the Dst index – one hour forward in relation to the last entered data – using the recurrent Elman neural network. The website of the Space Weather Analysis Center at SINP MSU provides online prediction of Dst index 0.51.5 hours ahead by the parameters of SW and IMF measured by the ACE spacecraft using ANN (http://swx.sinp.msu.ru/models/dst.php). The present paper is devoted to the comparison of the results of predicting the geomagnetic indices Dst, Kp and Ap with different horizons of the forecast among each other and with trivial models
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