A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results

Periods of high-speed streams associated with coronal holes, maximum solar-wind velocities, ratios of maximum to background solar-wind velocity, maximum Dst indices, and

Here we employ data from the solar wind monitors, WIND and ACE, and derive a linear relationship between the solar wind velocity and the cosmic noise absorption at IRIS for the

A standard approach to solar wind geoeffectiveness is to approximate an index with a combination of solar wind and IMF characteristics (driving function)... Optimal functions might

Using ptr3D, I was calculated for particles propagat- ing both forwards and backwards in time, during the same two periods of quiet and disturbed solar wind conditions as above

Abstract —This study aims to improve water level prediction at Bedup River with estimations made to absent precipitation data, both using Artificial Neural Network (ANN).. Studies

In this paper we present the temporal and spatial variations in TEC derived from the si- multaneous and continuous measurements made, for the first time, using the Indian GPS network

Considering the error of both GPS satel- lite and receiver instrumental biases based on the ionospheric model assumption, the accuracy of ionospheric absolute TEC derived from GPS

We then examine the variation of the solar wind ve- locity structure from 1998 (rising phase) to 2001 (after solar maximum), and compare our TST results with Ulysses solar