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1. Identity statement
Reference TypeBook Section
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3UL9GE2
Repositorysid.inpe.br/mtc-m21c/2019/12.27.10.12   (restricted access)
Last Update2019:12.27.10.12.30 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2019/12.27.10.12.30
Metadata Last Update2019:12.28.22.12.55 (UTC) administrator
Secondary KeyINPE--/
Citation KeySantosSouzMuraSant:2019:HyNeNe
TitleA hybrid neural network approach to estimate galaxy redshifts from multi-band photometric surveys
Year2019
Access Date2024, May 08
Secondary TypePRE LI
Number of Files1
Size4094 KiB
2. Context
Author1 Santos, Rafael Duarte Coelho dos
2 Souza, Felipe Carvalho de
3 Muralikrishna, Amita
4 Santos Júnior, Walter Augusto dos
Resume Identifier1 8JMKD3MGP5W/3C9JJ4N
Group1 LABAC-COCTE-INPE-MCTIC-GOV-BR
2 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
3 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 rafael.santos@inpe.br
2 felipe.carvalho@inpe.br
3 amita.muralikrishna@inpe.br
EditorTeuben, P. J.
Pound, M. W.
Thomas, B. A.
Warner, E. M.
Book TitleAstronomical data analysis software and systems XXVIII
PublisherAstronomical Society of the Pacific
Volume523
Pages103-106
Series TitleAstronomical Society of the Pacific Conference Series
History (UTC)2019-12-27 10:12:41 :: simone -> administrator :: 2019
2019-12-28 22:12:55 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsneural network
galaxy
AbstractMachine learning methods have been used in cosmological studies to estimate variables that would be hard or costly to measure precisely, like, for example, estimating redshifts from photometric data. Previous work showed good results for estimating photometric redshifts using nonlinear regression based on an artificial neural network (MultiLayer Perceptron or MLP). In this work we explore a hybrid neural network approach that uses a Self-Organizing Map (SOM) to separate the original data into different groups, then applying the MLP to each neuron on the SOM to obtain different regression models for each group. Preliminary results indicate that in some cases better results can be achieved, although the computational cost may be increased.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > A hybrid neural...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
Languageen
Target Filesantos_hybrid.pdf
User Groupsimone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2017/11.22.19.04.03
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3F2PHGS
DisseminationBNDEPOSITOLEGAL
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
Notes28th Annual Conference on Astronomical Data Analysis Software and Systems (ADASS XXVIII), 11-15 nov. 2018, University of Maryland, MD.
Empty Fieldsarchivingpolicy archivist callnumber city copyholder copyright creatorhistory descriptionlevel doi e-mailaddress edition format isbn issn label lineage mark nextedition numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype translator url
7. Description control
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