%0 Book Section
%@mirrorrepository urlib.net/www/2011/03.29.20.55
%3 souza_classification.pdf
%4 sid.inpe.br/plutao/2018/06.18.15.56.30
%A Souza, Vitor M.,
%A Medeiros, Cláudia,
%A Koga, Daiki,
%A Alves, Livia Ribeiro,
%A Vieira, Luís Eduardo Antunes,
%A Dal Lago, Alisson,
%A Silva, Ligia Alves da,
%A Jauer, Paulo Ricardo,
%A Baker, Daniel,
%B Machine learning techniques for space weather
%@secondarytype PRE LI
%D 2018
%E Camporeale, Enrico,
%E Johnson, Jay,
%E Wing, Simon,
%F lattes: 2470949000200852 4 SouzaMKAVDSJB:2018:ClMaPa
%I Elsevier
%K Self-organizing map, Pitch angle distribution, Earth’s magnetosphere.
%P 329-353
%T Classification of magnetospheric particle distributions via neural networks
%X In this chapter we introduce a special kind of neural network known as a self-organizing map (SOM) and use it to cluster/classify pitch angle-resolved particle flux data obtained by instruments onboard satellites orbiting the Earth. As an example of the technique, we employ electron flux data at both relativistic and subrelativistic energies provided by two instruments onboard one of the twin NASAs Van Allen Probes. For these data sets the SOM can identify the shapes of three well-known types of pitch angle distributions, and from that knowledge one can infer the associated physical mechanisms in the near-Earth space environment, particularly in the Van Allen radiation belts region. The SOM-based methodology can be used with multiplatform spacecraft data, thus enabling a prompt characterization of the physical processes throughout the Earths magnetosphere. The steps required to apply our neural network-based approach to pitch angle-resolved particle flux data from any spacecraft mission are laid out.
%@area CEA
%@electronicmailaddress
%@electronicmailaddress claudia.medeiros@inpe.br
%@electronicmailaddress daiki.koga@inpe.br
%@electronicmailaddress livia.alves@inpe.br
%@electronicmailaddress luis.vieira@inpe.br
%@electronicmailaddress alisson.dallago@inpe.br
%@electronicmailaddress ligia.silva@inpe.br
%@electronicmailaddress paulo.jauer@inpe.br
%@documentstage not transferred
%@group
%@group COCRC-COCRC-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@group DIDGE-CGCEA-INPE-MCTIC-GOV-BR
%@usergroup lattes
%@usergroup self-uploading-INPE-MCTI-GOV-BR
%@isbn 0128117893
%@nexthigherunit 8JMKD3MGPCW/3EU29DP 8JMKD3MGPCW/3F3PAJE
%@resumeid
%@resumeid
%@resumeid
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JGH3
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation University of Colorado Boulder
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@doi 10.1016/B978-0-12-811788-0.00013-5
%@tertiarymark Trabalho não Vinculado à Tese/Dissertação
%2 sid.inpe.br/plutao/2018/06.18.15.56.31