The Rule of Artificial Neural Network Algorithm in Geomagnetic Storms Prediction

While relativistic electrons can completely destroy a spacecraft when the solar wind-magnetospheric interactions are enhanced, the Dst index is considered to be an indicator of any geomagnetic storm. The more negative the Dst index values, the stronger the magnetic storm.   Every relativistic electron event was associated with a magnetic storm, but, magnetic storms could occur without appreciable enhancement of the relativistic electron fluxes. The problem thus arises, which one should be predicted:  the Dst index or relativistic electron enhancements (REE), in order to be more logic? and which is more effective for prediction: the use of statistical relationships or Artificial Neural Networks? Reproduction (or simulation) of the Dst index using a neural network algorithm would solve the problem. An Artificial Neural Network Algorithm was adopted in the present study for the reproduction of the Dst index of geomagnetic storms having the training concept “Train to Gain” in mind.  The ANN was well trained using a data set of 37 storms of different intensities as input to the network. A well trained ANN would yield an extremely good correlation between the measured Dst and the predicted Dst. The applied ANN algorithm in the present study shows an excellent performance. About 97% of the Dst have been reproduced, at least, for both the main and recovery phases. Efficient forecast of the oncoming relativistic electron flux enhancements (REE) can thus - under certain conditions - be issued. Keywords: Geomagnetic storms, Geosynchronous orbit, Solar cycle-23, Dst index, Relativistic Electron Enhancement, Artificial Neural Network

Relativistic Electron Enhancement (REE) Behavior during the Recovery Phase of Solar Cycle 23

To quantify the relationship between geomagnetic storms and relativistic electron enhancement (REE) at geosynchronous orbit and magnetic storms, a full solar cycle (1996–2006) of data has been examined.  The relativistic electron fluxes of the earth’s outer belt are subjected to strong temporal variations.  The most prominent changes are initiated by the fast solar wind streams which often also caused enhanced substorm activity and magnetic storms.  We considered the weak, moderate and intense geomagnetic storms using the index for 313 storms that occurred during Solar Cycle 23 (in the interval from January 1996 to December 2006).  The relativistic electron fluence data were based on fluxes observed by the GOES geosynchronous satellites. In the present study, we analyzed 313 Intense, Moderate and Weak storms observed at three different latitudes. A statistical study has been performed to quantify the REE behavior before and after the recovery phase of magnetic storms.  Every relativistic electron event was associated with a magnetic storm, but, magnetic storms could occur without appreciable enhancement of the relativistic electron fluxes.  More input parameters such as; solar wind velocity, dynamic pressure, and density, were thus used to make a cross-correlation analysis to determine what parameters might influence the flux of relativistic electrons. Keywords: Geomagnetic storms, Geosynchronous orbit, Dst index, Relativistic Electron Enhancement