Cart (Loading....) | Create Account
Close category search window
 

Improved prediction of IF2 and IG indices using neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Stamper, R. ; World Data Centre C1, Rutherford Appleton Lab., Chilton, UK

The paper presents an investigation into the use of artificial neural networks to predict the values of the IF2 and IG ionospheric indices. Since 1982, the World Data Centre C1 for Solar-Terrestrial Physics has produced predictions for these indices using an adaptation of the McNish-Lincoln (1949) technique for predicting sunspot numbers. It is demonstrated that significantly more accurate predictions are obtained using artificial neural networks, which form the basis of predictions which will in future be issued by the World Data Centre

Published in:

Microwaves, Antennas and Propagation, IEE Proceedings  (Volume:143 ,  Issue: 4 )

Date of Publication:

Aug 1996

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.