An automated method for detecting sporadic effects in cosmic rays
The paper proposes an automated method for analyzing data from neutron monitors and detecting sporadic effects in the dynamics of cosmic rays. The method is based on the use of LVQ neural networks and wavelet transform constructions. It is shown that the method allows detecting sporadic effects of d...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2020-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/56/e3sconf_strpep2020_02003.pdf |
| _version_ | 1818672573128376320 |
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| author | Geppener Vladimir Mandrikova Bogdana |
| author_facet | Geppener Vladimir Mandrikova Bogdana |
| author_sort | Geppener Vladimir |
| collection | DOAJ |
| description | The paper proposes an automated method for analyzing data from neutron monitors and detecting sporadic effects in the dynamics of cosmic rays. The method is based on the use of LVQ neural networks and wavelet transform constructions. It is shown that the method allows detecting sporadic effects of different amplitudes and durations and evaluating their parameters. A numerical implementation of procedures for detecting sporadic effects and assessing their intensity is carried out. The questions of choosing the parameters of algorithms are investigated and ways of their optimization are proposed. On the example of the April 13-14 2013 and March 8-9 2014 events, the effectiveness of the method for detecting sporadic effects in cosmic rays preceding and accompanying magnetic storms is shown. |
| first_indexed | 2024-12-17T07:42:02Z |
| format | Article |
| id | doaj.art-49376de9609244248003fb17da09535a |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-12-17T07:42:02Z |
| publishDate | 2020-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-49376de9609244248003fb17da09535a2022-12-21T21:58:06ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011960200310.1051/e3sconf/202019602003e3sconf_strpep2020_02003An automated method for detecting sporadic effects in cosmic raysGeppener Vladimir0Mandrikova Bogdana1Saint Petersburg Electrotechnical University “LETI”, 197022 Professora Popova st.Institute of Cosmophysical Research and Radio Wave Propagation FEB RASThe paper proposes an automated method for analyzing data from neutron monitors and detecting sporadic effects in the dynamics of cosmic rays. The method is based on the use of LVQ neural networks and wavelet transform constructions. It is shown that the method allows detecting sporadic effects of different amplitudes and durations and evaluating their parameters. A numerical implementation of procedures for detecting sporadic effects and assessing their intensity is carried out. The questions of choosing the parameters of algorithms are investigated and ways of their optimization are proposed. On the example of the April 13-14 2013 and March 8-9 2014 events, the effectiveness of the method for detecting sporadic effects in cosmic rays preceding and accompanying magnetic storms is shown.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/56/e3sconf_strpep2020_02003.pdf |
| spellingShingle | Geppener Vladimir Mandrikova Bogdana An automated method for detecting sporadic effects in cosmic rays E3S Web of Conferences |
| title | An automated method for detecting sporadic effects in cosmic rays |
| title_full | An automated method for detecting sporadic effects in cosmic rays |
| title_fullStr | An automated method for detecting sporadic effects in cosmic rays |
| title_full_unstemmed | An automated method for detecting sporadic effects in cosmic rays |
| title_short | An automated method for detecting sporadic effects in cosmic rays |
| title_sort | automated method for detecting sporadic effects in cosmic rays |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/56/e3sconf_strpep2020_02003.pdf |
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