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A hybrid total electron content forecasting model based on autoencoders and classical machine learning algorithms

Purpose. Development of a novel two-stage machine learning algorithm for total electron content (TEC) forecasting based on original TEC time series and influential external ionospheric parameters. Methods. Dimensionality reduction of the input data is performed using a standard fully-connected auto...

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Principais autores: Appalonov, Artem Mikhailovich, Maslennikova, Julia Sergeevna
Format: Artigo
Sprog:Inglês
Udgivet: Saratov State University 2026-03-01
Serier:Известия высших учебных заведений: Прикладная нелинейная динамика
Fag:
ionosphere
total electronic content
tec maps
solar activity
machine learning
neural networks
auto-coder
equatorial anomaly
Online adgang:https://andjournal.sgu.ru/sites/andjournal.sgu.ru/files/text-pdf/2026/03/and_2026-2_appalonov_maslennikova_286-298.pdf
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