Title of article
Equatorial predictions from a new neural network based global foF2 model Original Research Article
Author/Authors
L.A. McKinnell، نويسنده , , E.O. Oyeyemi، نويسنده ,
Issue Information
دوهفته نامه با شماره پیاپی سال 2010
Pages
8
From page
1016
To page
1023
Abstract
A new neural network (NN) based global empirical model for the foF2 parameter, which represents the peak ionospheric electron density, has been developed using extended temporal and spatial geophysical relevant inputs. It has been proposed that this new model be considered as a suitable replacement for the International Union of Radio Science (URSI) and International Radio Consultative Committee (CCIR) model options currently used within the International Reference Ionosphere (IRI) model for the purpose of F2 peak electron density predictions. The most recent version of the model has incorporated data from 135 global ionospheric stations including a number of equatorial stations.
This paper concentrates on the ability of this new model to predict foF2 for the equatorial sector, an area that has been identified as problematic within the current IRI peak prediction setup. The improvement in the predictions of the foF2 parameter by the new model as compared to the URSI and CCIR model options of the IRI is demonstrated and the requirement for additional foF2 data from the equatorial zone for the purpose of global modeling of foF2 is highlighted in this paper.
Article Outline
Keywords
Neural networks , Modeling , foF2 , IRI , Equatorial ionosphere
Journal title
Advances in Space Research
Serial Year
2010
Journal title
Advances in Space Research
Record number
1133143
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