Forecasting of ionospheric critical frequency using neural networks

Altinay O., Tulunay E., Tulunay Y.

GEOPHYSICAL RESEARCH LETTERS, cilt.24, sa.12, ss.1467-1470, 1997 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Konu: 12
  • Basım Tarihi: 1997
  • Doi Numarası: 10.1029/97gl01381
  • Sayfa Sayıları: ss.1467-1470


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.