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1. Identity statement
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 (UTC) marciana
Metadata Repositorycptec.inpe.br/walmeida/2004/06.24.14.34.11
Metadata Last Update2021:02.10.19.03.22 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyVijaykumarStePreCamNow:2002:OpNeNe
TitleOptimized Neural Network Code for Data Assimilation
FormatCD-ROM
Year2002
Access Date2025, July 04
Secondary TypePRE CN
Number of Files1
Size170 KiB
2. Context
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
Date4-9 ago.
Pages3841-3849
Book TitleAnais
Tertiary TypeArtigos
OrganizationSBMET
History (UTC)2008-06-10 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
2021-02-10 19:03:22 :: administrator -> marciana :: 2002
3. Content and structure
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.
AreaMET
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Optimized Neural Network...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDMD > Optimized Neural Network...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://mtc-m16b.sid.inpe.br/ibi/x6e6X3pFwXQZ3DUS8rS5/Cys5B
zipped data URLhttp://mtc-m16b.sid.inpe.br/zip/x6e6X3pFwXQZ3DUS8rS5/Cys5B
Languageen
User Groupadministrator
marciana
Reader Groupadministrator
marciana
Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/43SKC35
Citing Item Listsid.inpe.br/bibdigital/2013/09.22.23.14 1
Host Collectioncptec.inpe.br/walmeida/2003/04.25.17.12
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition editor electronicmailaddress isbn issn keywords label lineage mark mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject targetfile tertiarymark type url versiontype volume
7. Description control
e-Mail (login)marciana
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