Use of Artificial Neural Networks in precipitation forecasting of rainy season

Detalhes bibliográficos
Autor(a) principal: Dantas, Daniel
Data de Publicação: 2016
Outros Autores: Luz, Tarço Murilo Oliveira, Souza, Maria José Hatem de, Barbosa, Gabriela Paranhos, Cunha, Eduarda Gabriela Santos
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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spelling 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
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