1. Identity statement | |
Reference Type | Journal Article |
Site | plutao.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 8JMKD3MGP3W/3JJPDUT |
Repository | sid.inpe.br/plutao/2015/06.01.12.55.46 (restricted access) |
Last Update | 2015:07.06.17.35.55 (UTC) administrator |
Metadata Repository | sid.inpe.br/plutao/2015/06.01.12.55.47 |
Metadata Last Update | 2018:06.04.23.25.37 (UTC) administrator |
DOI | 10.17265/2159-5291/2015.05.005 |
ISSN | 2159-5291 |
Label | lattes: 2720072834057575 1 AnochiCamp:2015:ClPrPr |
Citation Key | AnochiCamp:2015:ClPrPr |
Title | Climate precipitation prediction by neural network |
Year | 2015 |
Access Date | 2024, May 17 |
Type of Work | journal article |
Secondary Type | PRE PI |
Number of Files | 1 |
Size | 3511 KiB |
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2. Context | |
Author | 1 Anochi, Juliana Aparecida 2 Campos Velho, Haroldo Fraga de |
Resume Identifier | 1 2 8JMKD3MGP5W/3C9JHC3 |
Group | 1 CAP-COMP-SPG-INPE-MCTI-GOV-BR 2 LAC-CTE-INPE-MCTI-GOV-BR |
Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) |
Author e-Mail Address | 1 juliana.anochi@gmail.com 2 haroldo@lac.inpe.br |
Journal | Journal of Mathematics and System Science |
Volume | 5 |
Pages | 207-213 |
History (UTC) | 2015-06-01 13:34:00 :: lattes -> administrator :: 2015 2018-06-04 23:25:37 :: administrator -> simone :: 2015 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Version Type | publisher |
Keywords | Climate Prediction Neural Networks Rough Sets Theory |
Abstract | In this work a neural network model for climate forecasting is presented. The model is built by training a neural network with available reanalysis data. In order to assess the model, the development methodology considers the use of data reduction strategies that eliminate data redundancy thus reducing the complexity of the models. The results presented in this paper considered the use of Rough Sets Theory principles in extracting relevant information from the available data to achieve the reduction of redundancy among the variables used for forecasting purposes. The paper presents results of climate prediction made with the use of the neural network based model. The results obtained in the conducted experiments show the effectiveness of the methodology, presenting estimates similar to observations. |
Area | COMP |
Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Climate precipitation prediction... |
Arrangement 2 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > Climate precipitation prediction... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
Language | pt |
User Group | lattes simone |
Reader Group | administrator simone |
Visibility | shown |
Read Permission | deny from all and allow from 150.163 |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | urlib.net/www/2011/03.29.20.55 |
Next Higher Units | 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPCW/3F2PHGS |
Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.49.40 3 sid.inpe.br/bibdigital/2013/10.12.22.16 1 sid.inpe.br/bibdigital/2013/09.22.23.14 1 |
URL (untrusted data) | http://www.davidpublisher.com/Home/Journal/JMSS |
Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
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6. Notes | |
Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress format isbn lineage mark month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject targetfile tertiarymark tertiarytype |
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7. Description control | |
e-Mail (login) | simone |
update | |
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