Neural Network Classification of the Cause–Effect Relationship between Substorm Activity and Structural Elements of Solar Wind Magnetic Clouds

Images are created of the causal relationship between substorm activity and the characteristics of such large-scale solar fluxes as magnetic clouds interacting with the Earth’s magnetosphere. An artificial neural network of the Kohonen layer type is used to classify these images. The results from cl...

Full description

Saved in:
Bibliographic Details
Published in:Bulletin of the Russian Academy of Sciences. Physics 2022-03, Vol.86 (3), p.256-261
Main Authors: Barkhatov, N. A., Vorobjev, V. G., Revunov, S. E., Barkhatova, O. M., Revunova, E. A., Yagodkina, O. I.
Format: Article
Language:English
Subjects:
Artificial neural networks
Earth magnetosphere
Hadrons
Heavy Ions
Image classification
Interplanetary magnetic field
Magnetic clouds
Neural networks
Nuclear Physics
Parameter identification
Perturbation
Physics
Physics and Astronomy
Saturn
Solar flux
Solar magnetic field
Solar wind
Structural members
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Images are created of the causal relationship between substorm activity and the characteristics of such large-scale solar fluxes as magnetic clouds interacting with the Earth’s magnetosphere. An artificial neural network of the Kohonen layer type is used to classify these images. The results from classification identify selected classes of substorms with perturbations in parameters of the solar wind and interplanetary magnetic field that are typical of structural elements of magnetic clouds.
ISSN:1062-8738
1934-9432
DOI:10.3103/S1062873822030054