Evolutionary Prediction of Total Electron Content over Cyprus

Abstract : Total Electron Content (TEC) is an ionospheric characteristic used to derive the signal delay imposed by the ionosphere on trans-ionospheric links and subsequently overwhelm its negative impact in accurate position determination. In this paper, an Evolutionary Algorithm (EA), and particularly a Genetic Programming (GP) based model is designed. The proposed model is based on the main factors that influence the variability of the predicted parameter on a diurnal, seasonal and long-term time-scale. Experimental results show that the GP-model, which is based on TEC measurements obtained over a period of 11 years, has produced a good approximation of the modeled parameter and can be implemented as a local model to account for the ionospheric imposed error in positioning. The GP-based approach performs better than the existing Neural Network-based approach in several cases.
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Alexandros Agapitos, Andreas Konstantinidis, Haris Haralambous, Harris Papadopoulos. Evolutionary Prediction of Total Electron Content over Cyprus. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. pp.387-394, ⟨10.1007/978-3-642-16239-8_50⟩. ⟨hal-01060640⟩

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