Use of Artificial Neural Networks in precipitation forecasting of rainy season
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista Espinhaço |
Texto Completo: | https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/82 |
Resumo: | This study aims to estimate the precipitation in the rainy season in Diamantina (MG) based on precipitation of dry previous seasons, by using Artificial Neural Networks (ANN). The chronological order of the data was changed so that the dry season of and year was related to the rainy season of the next year. A part of the data was used in the ANN training and other part used to evaluate the performance of it. The used analysis was time series and the best network found was of radial basis function type. The ANN found showed an average of error of 10%. The average precipitation of the period used in application of the network was of 1099 mm, while the average estimation was 1128 mm. The use of dry season’s data to estimate the precipitation of the rainy season presented satisfactory results and, the change of the chronological order of the dry period result in a neural network with more effective forecasting despite the unchanged one. |
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Use of Artificial Neural Networks in precipitation forecasting of rainy seasonUso de Redes Neurais Artificiais na previsão da precipitação de períodos chuvososCenários climáticosmodelagem do climaprevisão do tempoClimatic sceneriesclimate modelingweather forecastingThis study aims to estimate the precipitation in the rainy season in Diamantina (MG) based on precipitation of dry previous seasons, by using Artificial Neural Networks (ANN). The chronological order of the data was changed so that the dry season of and year was related to the rainy season of the next year. A part of the data was used in the ANN training and other part used to evaluate the performance of it. The used analysis was time series and the best network found was of radial basis function type. The ANN found showed an average of error of 10%. The average precipitation of the period used in application of the network was of 1099 mm, while the average estimation was 1128 mm. The use of dry season’s data to estimate the precipitation of the rainy season presented satisfactory results and, the change of the chronological order of the dry period result in a neural network with more effective forecasting despite the unchanged one.O estudo objetiva estimar a precipitação na estação chuvosa em Diamantina (MG) com base na precipitação das estações secas anteriores por meio de Redes Neurais Artificiais (RNA). Alterou-se a ordem cronológica dos dados de forma que o período seco de um ano estivesse relacionado com o período chuvoso do ano seguinte. Utilizou-se parte dos dados no treinamento e parte na avaliação do desempenho da RNA. Utilizou-se a análise do tipo séries temporais e a melhor rede encontrada foi do tipo função de base radial. A RNA apresentou um erro médio de 10%. A média de precipitação no período de aplicação da rede foi 1.099 mm, enquanto a estimativa média foi 1.128 mm. A utilização de dados dos períodos secos para estimar a precipitação no período chuvoso apresenta resultados satisfatórios e a alteração na ordem cronológica do período seco resultou em uma rede com previsão mais eficaz.UFVJM2016-06-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigo avaliado pelos Paresapplication/pdfhttps://revistas.ufvjm.edu.br/revista-espinhaco/article/view/8210.5281/zenodo.3958064Revista Espinhaço ; Revista Espinhaço #82317-0611reponame:Revista Espinhaçoinstname:Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)instacron:UFVJMporhttps://revistas.ufvjm.edu.br/revista-espinhaco/article/view/82/87Copyright (c) 2022 Revista Espinhaço https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessDantas, DanielLuz, Tarço Murilo OliveiraSouza, Maria José Hatem deBarbosa, Gabriela ParanhosCunha, Eduarda Gabriela Santos2022-07-22T18:45:15Zoai:ojs.pkp.sfu.ca:article/82Revistahttps://revistaespinhaco.com/index.php/revista/indexPUBhttps://revistas.ufvjm.edu.br/revista-espinhaco/oairevista.espinhaco@gmail.com || doug.sathler@gmail.com2317-06112317-0611opendoar:2022-07-22T18:45:15Revista Espinhaço - Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)false |
dc.title.none.fl_str_mv |
Use of Artificial Neural Networks in precipitation forecasting of rainy season Uso de Redes Neurais Artificiais na previsão da precipitação de períodos chuvosos |
title |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
spellingShingle |
Use of Artificial Neural Networks in precipitation forecasting of rainy season Dantas, Daniel Cenários climáticos modelagem do clima previsão do tempo Climatic sceneries climate modeling weather forecasting |
title_short |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
title_full |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
title_fullStr |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
title_full_unstemmed |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
title_sort |
Use of Artificial Neural Networks in precipitation forecasting of rainy season |
author |
Dantas, Daniel |
author_facet |
Dantas, Daniel Luz, Tarço Murilo Oliveira Souza, Maria José Hatem de Barbosa, Gabriela Paranhos Cunha, Eduarda Gabriela Santos |
author_role |
author |
author2 |
Luz, Tarço Murilo Oliveira Souza, Maria José Hatem de Barbosa, Gabriela Paranhos Cunha, Eduarda Gabriela Santos |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Dantas, Daniel Luz, Tarço Murilo Oliveira Souza, Maria José Hatem de Barbosa, Gabriela Paranhos Cunha, Eduarda Gabriela Santos |
dc.subject.por.fl_str_mv |
Cenários climáticos modelagem do clima previsão do tempo Climatic sceneries climate modeling weather forecasting |
topic |
Cenários climáticos modelagem do clima previsão do tempo Climatic sceneries climate modeling weather forecasting |
description |
This study aims to estimate the precipitation in the rainy season in Diamantina (MG) based on precipitation of dry previous seasons, by using Artificial Neural Networks (ANN). The chronological order of the data was changed so that the dry season of and year was related to the rainy season of the next year. A part of the data was used in the ANN training and other part used to evaluate the performance of it. The used analysis was time series and the best network found was of radial basis function type. The ANN found showed an average of error of 10%. The average precipitation of the period used in application of the network was of 1099 mm, while the average estimation was 1128 mm. The use of dry season’s data to estimate the precipitation of the rainy season presented satisfactory results and, the change of the chronological order of the dry period result in a neural network with more effective forecasting despite the unchanged one. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-06-04 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artigo avaliado pelos Pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/82 10.5281/zenodo.3958064 |
url |
https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/82 |
identifier_str_mv |
10.5281/zenodo.3958064 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/82/87 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Revista Espinhaço https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Revista Espinhaço https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UFVJM |
publisher.none.fl_str_mv |
UFVJM |
dc.source.none.fl_str_mv |
Revista Espinhaço ; Revista Espinhaço #8 2317-0611 reponame:Revista Espinhaço instname:Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM) instacron:UFVJM |
instname_str |
Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM) |
instacron_str |
UFVJM |
institution |
UFVJM |
reponame_str |
Revista Espinhaço |
collection |
Revista Espinhaço |
repository.name.fl_str_mv |
Revista Espinhaço - Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM) |
repository.mail.fl_str_mv |
revista.espinhaco@gmail.com || doug.sathler@gmail.com |
_version_ |
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