Forecasting of ionospheric critical frequency using neural networks

Details Forecasting of ionospheric critical frequency using neural networks Forecasting of ionospheric critical frequency using neural networks

Jun 1997

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997georl..24.1467a&link_type=abstract

Geophysical Research Letters, Volume 24, Issue 12, p. 1467-1470

Physics

23

Ionosphere: Modeling And Forecasting, Ionosphere: Wave Propagation, Radio Science: Radio Wave Propagation, Radio Science: Ionospheric Physics

Scientific paper

Multilayer perceptron type neural networks (NN) are employed for forecasting ionospheric critical frequency (foF2) one hour in advance. The nonlinear black-box modeling approach in system identification is used. The main contributions: 1. A flexible and easily accessible training database capable of handling extensive physical data is prepared, 2. Novel NN design and experimentation software is developed, 3. A training strategy is adopted in order to significantly enhance the generalization or extrapolation ability of NNs, 4. A method is developed for determining the relative significances (RS) of NN inputs in terms of mapping capability.

Affiliated with

Also associated with

No associations

Rating

Forecasting of ionospheric critical frequency using neural networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Forecasting of ionospheric critical frequency using neural networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Forecasting of ionospheric critical frequency using neural networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1474200