Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors
Abstract The objective of this work is to perform a comparative flow forecast for the Orós basin (Ceará, Brazil) using artificial neural networks (RNA) and k-neighbors re-sampling technique. The models were developed from the historical series of 100 years of hydrometeorological data (sea surface te...
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ftsmithonian:oai:figshare.com:article/14282000 2023-05-15T17:33:15+02:00 Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors Carla Beatriz Costa de Araújo (10393085) Francisco de Assis de Souza Filho (6125513) Luiz Martins de Araújo Júnior (6125516) Cleiton da Silva Silveira (6122690) 2020-06-01T08:47:44Z https://doi.org/10.6084/m9.figshare.14282000.v1 unknown https://figshare.com/articles/dataset/Seasonal_Flow_Forecast_for_the_Or_s_Dam_Cear_Brazil_Using_Neural_Networks_and_the_Resampling_Technique_of_K-neighbors/14282000 doi:10.6084/m9.figshare.14282000.v1 CC BY 4.0 CC-BY Meteorology models streamflow forecasting Oros reservoir Dataset 2020 ftsmithonian https://doi.org/10.6084/m9.figshare.14282000.v1 2021-04-11T16:48:04Z Abstract The objective of this work is to perform a comparative flow forecast for the Orós basin (Ceará, Brazil) using artificial neural networks (RNA) and k-neighbors re-sampling technique. The models were developed from the historical series of 100 years of hydrometeorological data (sea surface temperature and flows). Both use as predictors the temperatures of the North Atlantic, South Atlantic and Equatorial Pacific oceans, and forecast July in the next year’s rainy season (January to June). The k-neighbors model was elaborated from the identification of the closest neighbor years for the resampling of the approximation, since the RNA model was formulated from the synaptic and bias weights obtained in the training phase of the network. The Nash-Suttcliffe (E) efficiency coefficient, the coefficient of determination (R²), the Taylor diagram (2001) and the coefficient of determination (R²) were used for the validation step. maximum likelihood ratio. For all comparative variables, the neural model presented better values, indicating that this represents more efficiently the behavior of the flows to the reservoir. Dataset North Atlantic Unknown Pacific Nash ENVELOPE(-62.350,-62.350,-74.233,-74.233) |
institution |
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op_collection_id |
ftsmithonian |
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unknown |
topic |
Meteorology models streamflow forecasting Oros reservoir |
spellingShingle |
Meteorology models streamflow forecasting Oros reservoir Carla Beatriz Costa de Araújo (10393085) Francisco de Assis de Souza Filho (6125513) Luiz Martins de Araújo Júnior (6125516) Cleiton da Silva Silveira (6122690) Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
topic_facet |
Meteorology models streamflow forecasting Oros reservoir |
description |
Abstract The objective of this work is to perform a comparative flow forecast for the Orós basin (Ceará, Brazil) using artificial neural networks (RNA) and k-neighbors re-sampling technique. The models were developed from the historical series of 100 years of hydrometeorological data (sea surface temperature and flows). Both use as predictors the temperatures of the North Atlantic, South Atlantic and Equatorial Pacific oceans, and forecast July in the next year’s rainy season (January to June). The k-neighbors model was elaborated from the identification of the closest neighbor years for the resampling of the approximation, since the RNA model was formulated from the synaptic and bias weights obtained in the training phase of the network. The Nash-Suttcliffe (E) efficiency coefficient, the coefficient of determination (R²), the Taylor diagram (2001) and the coefficient of determination (R²) were used for the validation step. maximum likelihood ratio. For all comparative variables, the neural model presented better values, indicating that this represents more efficiently the behavior of the flows to the reservoir. |
format |
Dataset |
author |
Carla Beatriz Costa de Araújo (10393085) Francisco de Assis de Souza Filho (6125513) Luiz Martins de Araújo Júnior (6125516) Cleiton da Silva Silveira (6122690) |
author_facet |
Carla Beatriz Costa de Araújo (10393085) Francisco de Assis de Souza Filho (6125513) Luiz Martins de Araújo Júnior (6125516) Cleiton da Silva Silveira (6122690) |
author_sort |
Carla Beatriz Costa de Araújo (10393085) |
title |
Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
title_short |
Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
title_full |
Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
title_fullStr |
Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
title_full_unstemmed |
Seasonal Flow Forecast for the Orós Dam (Ceará, Brazil) Using Neural Networks and the Resampling Technique of K-neighbors |
title_sort |
seasonal flow forecast for the orós dam (ceará, brazil) using neural networks and the resampling technique of k-neighbors |
publishDate |
2020 |
url |
https://doi.org/10.6084/m9.figshare.14282000.v1 |
long_lat |
ENVELOPE(-62.350,-62.350,-74.233,-74.233) |
geographic |
Pacific Nash |
geographic_facet |
Pacific Nash |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://figshare.com/articles/dataset/Seasonal_Flow_Forecast_for_the_Or_s_Dam_Cear_Brazil_Using_Neural_Networks_and_the_Resampling_Technique_of_K-neighbors/14282000 doi:10.6084/m9.figshare.14282000.v1 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.14282000.v1 |
_version_ |
1766131690439180288 |