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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2021, Volume 61, Number 7, Pages 1137–1148
DOI: https://doi.org/10.31857/S0044466921070061 (Mi zvmmf11264) 		 
This article is cited in 4 scientific papers (total in 4 papers)

Computer science

Automated method for cosmic ray data analysis and detection of sporadic effects

V. V. Geppenera, B. S. Mandrikovab

a St. Petersburg Electrotechnical University "LETI", 197022, St. Petersburg, Russia
b Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch, Russian Academy of Sciences, 684034, Kamchatka Region, Russia
Citations (4)
DOI: https://doi.org/10.31857/S0044466921070061
Abstract: An automated method for detecting multiscale sporadic effects in data from ground-based neutron monitors is proposed. The method is based on the wavelet transform and neural networks of learning vector quantization type (LVQ neural networks). The choice of Daubechies wavelets and Coiflets at the data preprocessing stage is justified. An algorithm for choosing the “best” approximating wavelet basis in the class of orthogonal functions is proposed. The effectiveness of the method as applied to the detection of small-scale sporadic effects is shown experimentally. The possibility of a numerical implementation of the method for operational use is demonstrated.
Key words: data analysis method, LVQ neural networks, wavelet transform, cosmic rays, sporadic effects.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation AAAA-A21-121011290003-0
This study was carried out within the state assignment on the subject “Physical processes in the system of near space and geospheres under solar and lithospheric influences” (2021–2023), state registration no. AAAA-A21-121011290003-0.
Received: 26.11.2020
Revised: 26.11.2020
Accepted: 11.03.2021
English version:
Computational Mathematics and Mathematical Physics, 2021, Volume 61, Issue 7, Pages 1129–1139
DOI: https://doi.org/10.1134/S096554252107006X
Bibliographic databases:
Document Type: Article
UDC: 519.72
Language: Russian
Citation: V. V. Geppener, B. S. Mandrikova, “Automated method for cosmic ray data analysis and detection of sporadic effects”, Zh. Vychisl. Mat. Mat. Fiz., 61:7 (2021), 1137–1148; Comput. Math. Math. Phys., 61:7 (2021), 1129–1139
Citation in format AMSBIB
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\issue 7
\pages 1137--1148
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    • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    		Журнал вычислительной математики и математической физики Computational Mathematics and Mathematical Physics
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