%0 Journal Article
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@nexthigherunit 8JMKD3MGPCW/3ETL868
%@archivingpolicy denypublisher denyfinaldraft
%@resumeid
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JGKH
%X The inverse problem to retrieve useful airglow volume emission rate profiles from rocket-borne photometer measurements has been solved by adopting the well-characterized spectral photometric methods. An alternative recovery method based on artificial neural network (ANN) is presented. A multilayer perceptron neural network was trained with available experimental and synthetic data. Integrated emissions profiles measured by a rocket experiment were taken as the input data. From the results obtained in this work, it may be concluded that the ANN technique is a convenient tool to recover volume emission rate profiles.
%@mirrorrepository sid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
%N 2
%T A representative airglow volume emisson profile from rocket-borne photometer data by an artificial neural network technique
%@secondarytype PRE PN
%K applied computing in space and environmental sciences, neural networks, inverse problem, airglow, rocket.
%@usergroup administrator
%@usergroup secretaria.cpa@dir.inpe.br
%@group DAE-CEA-INPE-MCT-BR
%@group
%@group
%@group DAE-CEA-INPE-MCT-BR
%@e-mailaddress secretaria.cpa@dir.inpe.br
%@secondarykey INPE--PRE/
%@issn 1983-8409
%@issn 2177-8833
%2 sid.inpe.br/mtc-m19/2012/01.02.16.29.24
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto de Estudos Avançados, Instituto de Estudos Avançados do DCTA
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%B Journal of Computational Interdisciplinary Sciences
%P  1-11
%4 sid.inpe.br/mtc-m19/2012/01.02.16.29
%@documentstage not transferred
%D 2011
%V 2
%A Meneses, Francisco Carlos de,
%A Shiguemori, Elcio Hideiti,
%A Muralikrishnaa, P.,
%A Clemesha, Barclay Robert,
%@area CEA