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...
Main Authors: | Geppener Vladimir, Mandrikova Bogdana |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2020-01-01
|
Series: | E3S Web of Conferences |
Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/56/e3sconf_strpep2020_02003.pdf |
Similar Items
-
Estimation of the state of the cosmic ray flux based on neural networks
by: Mandrikova Bogdana, et al.
Published: (2020-01-01) -
Analysis of cosmic ray dynamics and ionospheric parameters during increased solar activity and magnetic storms
by: Mandrikova Oksana, et al.
Published: (2019-01-01) -
Detection on Cosmic-Ray Neutron
by: Yeh, Chun Chao, et al.
Published: (1994) -
Detection of Cosmic-Ray Ensembles with CREDO
by: Woźniak Krzysztof W.
Published: (2019-01-01) -
Method of Constructing a Nonlinear Approximating Scheme of a Complex Signal: Application Pattern Recognition
by: Oksana Mandrikova, et al.
Published: (2021-03-01)