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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Repositorysid.inpe.br/mtc-m18@80/2008/09.29.19.53   (restricted access)
Last Update2008:10.13.11.23.06 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m18@80/2008/09.29.19.53.18
Metadata Last Update2018:06.04.04.05.33 (UTC) administrator
Secondary KeyINPE-15635-PRE/10360
Citation KeySousaSous:2008:MoHiRe
TitleModelagem hidrológica com rede neural artificial para a bacia hidrográfica do rio Piancó
FormatCD-ROM
Year2008
Secondary Date20080824
Access Date2024, Apr. 19
Secondary TypePRE CN
Number of Files1
Size77 KiB
2. Context
Author1 Sousa, Wanderson dos S.
2 Sousa, Francisco de A. S. de
Group1 CST-CST-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE/CPTEC)
2 UACA/CTRN/UFCG - Campina Grande, PB
e-Mail Addressdeicy@cptec.inpe.br
Conference NameCongresso Brasileiro de Meteorologia, 15.
Conference LocationSão Paulo
Date24-29 ago
Book TitleAnais
Tertiary TypeArtigo
OrganizationSBMET
History (UTC)2008-12-17 14:06:11 :: deicy -> administrator ::
2018-06-04 04:05:33 :: administrator -> marciana :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsHidrometeorologia
rede neural artificial
processo chuva-vazão
AbstractA previsão de vazão em um sistema hídrico é uma das técnicas utilizadas para minimizar o impacto das incertezas do clima sobre o gerenciamento dos recursos hídricos. Essa técnica pode ser considerada um dos principais desafios relacionados ao conhecimento integrado da climatologia e da hidrologia de uma bacia hidrográfica. O objetivo deste trabalho foi o de modelar a relação não-linear entre chuva e vazão na bacia hidrográfica do rio Piancó, no semi-árido paraibano, utilizando a técnica de Redes Neurais Artificiais (RNA). Aqui foi avaliada a capacidade da RNA modelar o processo chuva-vazão em base mensal. Considerou-se durante o treinamento da RNA a influência da arquitetura da rede e da inicialização dos pesos. No final do treinamento foi escolhida a melhor arquitetura, para modelar vazões médias mensais na bacia estudada, com base no desempenho do modelo. A arquitetura de RNA que produziu melhor resultado foi a RC315L com valores para o coeficiente de determinação, de eficiência e erro padrão da estimativa de 92,0 %, 77,0 % e 8,29 respectivamente. ABSTRACT: The streamflow forecasting in a water system is one of the techniques used to reduce impact of the uncertainties of the climate on administration of the water resources. That technique can be considered one of the principal challenges related to the integrated knowledge of the climatology and of the hydrology of the river basin. The aim of this work was it of modeling the no-linear relation between rainfall and streamflow in the Piancó river basin, in the paraibano semiarid, using the technique of Artificial Neural Networks (ANN). Here the ability of ANN was evaluated to model the rainfall-runoff process in monthly base. It was considered, during training of ANN, the network architecture and, weights initialization influence. In the end of the training it was chosen the best architecture, to model the streamflow monthly mean in the studied basin, with base in the acting of the model. The architecture of ANN that produced better result was RC315L with values for the determination coefficient, efficiency coefficient and standard estimate error (SEE) equal to 92.0%, 77.0% and 8.29 respectively.
AreaMET
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > COCST > Modelagem hidrológica com...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languagept
Target FileModelagem hidrologica.pdf
User Groupadministrator
deicy
administrator
Visibilityshown
Copy HolderSID/SCD
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Next Higher Units8JMKD3MGPCW/3F3T29H
Host Collectionsid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyright creatorhistory descriptionlevel dissemination documentstage doi edition editor electronicmailaddress identifier isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup resumeid rightsholder schedulinginformation secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
7. Description control
e-Mail (login)marciana
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