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Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m16b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifierx6e6X3pFwXQZ3DUS8rS5/Cys5B
Repositorycptec.inpe.br/walmeida/2004/06.24.14.34
Last Update2015:11.18.17.41.27 marciana
Metadatacptec.inpe.br/walmeida/2004/06.24.14.34.11
Metadata Last Update2018:06.05.03.51.12 administrator
Secondary KeyINPE--PRE/
Citation KeyVijaykumarStePreCamNow:2002:OpNeNe
TitleOptimized Neural Network Code for Data Assimilation
FormatCD-ROM
Year2002
Date4-9 ago.
Access Date2021, Jan. 18
Number of Files1
Size170 KiB
Context area
Author1 Vijaykumar, Nandamudi Lankalapali
2 Stephanyl, Stephan
3 Preto, Airam Jonatas
4 Campos Velho, Haroldo Fraga de
5 Nowosad, Alexandre G.
Group1 LAC-INPE-MCT-BR
2 DMD-INPE-MCT-BR
Affiliation1 INPE-Sao Jose dos Campos-12227-010-SP-Brasil
e-Mail Addressfabia@cptec.inpe.br
Conference NameCongresso Brasileiro de Meteorologia, 12.
Conference LocationFoz do Iguacu
Pages3841-3849
Book TitleAnais
Secondary TypePRE CN
Tertiary TypeArtigos
OrganizationSBMET
History2008-06-10 21:14:27 :: administrator -> estagiario ::
2010-05-11 16:53:48 :: estagiario -> administrator ::
2013-09-22 23:27:12 :: administrator -> marciana :: 2002
2014-10-24 16:31:28 :: marciana -> administrator :: 2002
2015-03-04 14:04:57 :: administrator -> marciana :: 2002
2015-11-18 17:41:27 :: marciana -> administrator :: 2002
2018-06-05 03:51:12 :: administrator -> marciana :: 2002
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
AbstractThe data assimilation process can be described as a procedure that uses observational data to improve the prediction made by an inaccurate mathematical modelo Recent1y, neural networks have been proposed as a new method for data assimilation. The Multilayer Perceptron network with backpropagation learning was chosen for this procedure. Neural networks are inherent1y a parallel procedure. This paper presents some strategies being used to achieve an optimized parallel code for the network training. Code optimizations include the use of either High Perfonnance Fortran directives or Message Passing Interface library calls. A neural network for Data Assimilation was trained based on both the physical models of the Lorenz and shallow water equations.
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data URLhttp://mtc-m16b.sid.inpe.br/rep/x6e6X3pFwXQZ3DUS8rS5/Cys5B
zipped data URLhttp://mtc-m16b.sid.inpe.br/zip/x6e6X3pFwXQZ3DUS8rS5/Cys5B
Languageen
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marciana
Reader Groupadministrator
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Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
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Next Higher Units8JMKD3MGPCW/3ESGTTP
Host Collectioncptec.inpe.br/walmeida/2003/04.25.17.12
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