A Neural Network for Spatial and Temporal Modeling of foF2 Data Based on Satellite Measurements

Abstract : This paper presents the application of Neural Networks for the spatial and temporal modeling of (critical frequency) foF2 data over Europe. foF2 is the most important parameter in describing the electron density profile of the ionosphere since it represents the critical point of maximum electron density in the profile and therefore can be used to drive empirical models of electron density which incorporate foF2 as an anchor point in the profile shape. The model is based on radio occultation (RO) measurements by LEO (Low Earth Orbit) satellites which provide excellent spatial coverage of foF2 measurements.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.224-233, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_24〉
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Haris Haralambous, Harris Papadopoulos. A Neural Network for Spatial and Temporal Modeling of foF2 Data Based on Satellite Measurements. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.224-233, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_24〉. 〈hal-01521412〉

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