Short-term prediction of fof2 using time-delay neural network

To test the ability and efficacy of neural networks in short-term prediction of ionospheric parameters, this study used the time series of the ionospheric foF2 data from Slough station during solar cycles 21 and 22. It describes different neural network architectures that led to similar conclusions...

Full description

Saved in:
Bibliographic Details
Published in:Physics and chemistry of the earth. Part C, Solar-terrestrial and planetary science Solar-terrestrial and planetary science, 1999-01, Vol.24 (4), p.343-347
Main Authors: Wintoft, P., Cander, Lj.R.
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:To test the ability and efficacy of neural networks in short-term prediction of ionospheric parameters, this study used the time series of the ionospheric foF2 data from Slough station during solar cycles 21 and 22. It describes different neural network architectures that led to similar conclusions on one-hour-ahead foF2 prediction. This prediction is compared with observations and results from linear and persistence models considered here as two special cases of the neural networks.
ISSN:1464-1917
DOI:10.1016/S1464-1917(99)00009-4