A neural network study of the mapping from solar magnetic fields to the daily average solar wind velocity
- 1 April 1999
- journal article
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research
- Vol. 104 (A4) , 6729-6736
- https://doi.org/10.1029/1998ja900183
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- Response of the auroral electrojets to the solar wind modeled with neural networksJournal of Geophysical Research, 1997
- Prediction of daily average solar wind velocity from solar magnetic field observations using hybrid intelligent systemsPhysics and Chemistry of the Earth, 1997
- On calculating the solar wind parameters from the solar magnetic field dataAstronomical & Astrophysical Transactions, 1996
- Solar origin of geomagnetic storms and prediction of storms with the use of neural networksSurveys in Geophysics, 1996
- Predicting geomagnetic storms from solar-wind data using time-delay neural networksAnnales Geophysicae, 1996
- Prediction of geomagnetic storms from solar wind data using Elman Recurrent Neural NetworksGeophysical Research Letters, 1996
- Prediction of geomagnetic storms from solar wind data with the use of a neural networkAnnales Geophysicae, 1994
- Orthogonal least squares learning algorithm for radial basis function networksIEEE Transactions on Neural Networks, 1991
- Networks for approximation and learningProceedings of the IEEE, 1990
- Solar wind speed and coronal flux-tube expansionThe Astrophysical Journal, 1990