Predictions of SEP events by means of a linear filter and layer-recurrent neural network

0365304 - GFÚ 2012 RIV GB eng J - Journal Article
Valach, F. - Revallo, M. - Hejda, Pavel - Bochníček, Josef
Predictions of SEP events by means of a linear filter and layer-recurrent neural network.
Acta Astronautica. Roč. 69, č. 9-10 (2011), s. 758-766. ISSN 0094-5765. E-ISSN 1879-2030
R&D Projects: GA AV ČR(CZ) IAA300120608; GA MŠMT OC09070
Grant - others:VEGA(SK) 2/0015/11; VEGA(SK) 2/0022/11
Institutional research plan: CEZ:AV0Z30120515
Keywords : coronal mass ejection * X-ray flare * solar energetic particles * artificial neural network
Subject RIV: DE - Earth Magnetism, Geodesy, Geography
Impact factor: 0.614, year: 2011

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.
Permanent Link: http://hdl.handle.net/11104/0200577