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Predictions of SEP events by means of a linear filter and layer-recurrent neural network
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SYSNO ASEP 0365304 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Predictions of SEP events by means of a linear filter and layer-recurrent neural network Author(s) Valach, F. (SK)
Revallo, M. (SK)
Hejda, Pavel (GFU-E) ORCID, RID
Bochníček, Josef (GFU-E) ORCID, RIDSource Title Acta Astronautica. - : Elsevier - ISSN 0094-5765
Roč. 69, č. 9-10 (2011), s. 758-766Number of pages 9 s. Language eng - English Country GB - United Kingdom Keywords coronal mass ejection ; X-ray flare ; solar energetic particles ; artificial neural network Subject RIV DE - Earth Magnetism, Geodesy, Geography R&D Projects IAA300120608 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) OC09070 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z30120515 - GFU-E (2005-2011) UT WOS 000295069600002 DOI 10.1016/j.actaastro.2011.06.003 Annotation Solar energetic particle (SEP) modelling has gained great interest in the community, specifically in connection with the safety of crews and the protection of technological systems of spacecraft situated outside the shielding of Earth's magnetosphere. Two models for the prediction of SEP events are presented in this paper. The models are based on a linear filter and on a special type of dynamic artificial neural network known as the layer-recurrent neural network. In this work they use as input the following parameters: the X-ray flare class for flares originating close to the centre of the solar disk; observed type II or IV radio bursts; and of the position angle, width, and linear speed of observed full or partial halo CMEs. Workplace Geophysical Institute Contact Hana Krejzlíková, kniha@ig.cas.cz, Tel.: 267 103 028 Year of Publishing 2012
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