Prediction of D variations from Polar Cap indices using time-delay neural network

Details Prediction of D variations from Polar Cap indices using time-delay neural network Prediction of D variations from Polar Cap indices using time-delay neural network

Dec 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005jastp..67.1658s&link_type=abstract

Journal of Atmospheric and Terrestrial Physics, v. 67, iss. 17-18 [SPECIAL ISSUE], p. 1658-1664.

Physics

1

Scientific paper

The hourly averaged Polar Cap (PC) index was used as the input parameter for the ring current index D variation forecasting. The PC index is known to describe well the principal features of the interplanetary magnetic field as well as the total energy input to the magnetosphere. This allowed us to design a neural network that was able to forecast the D variations 1 h ahead. 1995 PC and D data sets were used for training and testing and 1997 data sets were used for validation. From 15 moderate and strong geomagnetic storms observed during 1997, 10 were successfully forecasted. In 3 cases the observed minimum D value was less than the predicted value, and only in 3 cases the neural network was not able to reproduce the features of the geomagnetic storm.

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