Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/112397
Title: Total Electron Content PCA-NN Prediction Model for South-European Middle Latitudes
Authors: Morozova, A. L. 
Barata, Teresa 
Barlyaeva, Tatiana 
Gafeira, Ricardo 
Keywords: ionosphere; total electron content prediction; middle latitudes; neural networks; spaceweather
Issue Date: 2023
Publisher: MDPI
Serial title, monograph or event: Atmosphere
Volume: 14
Issue: 7
Abstract: A regression-based model was previously developed to forecast total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype simulates and forecasts TEC variations in relation to space weather conditions. The development of a prototype consisted of the selection of the best set of predictors, NN architecture, and the length of the input series. Tests made using the data from December 2014 to June 2018 show that the PCA-NN model based on a simple feed-forward NN with a very limited number (up to six) of space weather predictors performs better than the PCA-MRM model that uses up to 27 space weather predictors. The prototype is developed on a TEC series obtained from a GNSS receiver at Lisbon airport and tested on TEC series from three other locations at middle latitudes of the Eastern North Atlantic. Conclusions on the dependence of the forecast quality on longitude and latitude are made.
URI: https://hdl.handle.net/10316/112397
ISSN: 2073-4433
DOI: 10.3390/atmos14071058
Rights: openAccess
Appears in Collections:I&D CITEUC - Artigos em Revistas Internacionais
FCTUC Física - Artigos em Revistas Internacionais
FCTUC Ciências da Terra - Artigos em Revistas Internacionais

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