Monthly rainfall forecast study in southeastern Brazil using multi-layer perceptron (MLP) neural networks
This work uses the MLP neural network technique to make monthly rainfall forecast estimates for Guarulhos airport in southeastern Brazil using a time series of approximately 70 years. Neural network structures with two or more hidden layers showed a better result, minimizing the prediction error.
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | Brasil |
| Institución: | Universidade Federal de Santa Maria (UFSM) |
| Repositorio: | Revista Ciência e Natura (Online) |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/45220 |
| Acceso en línea: | https://periodicos.ufsm.br/cienciaenatura/article/view/45220 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural network Time series Monthly Rainfall Rede neural Séries temporais Precipitação mensal |
| Sumario: | This work uses the MLP neural network technique to make monthly rainfall forecast estimates for Guarulhos airport in southeastern Brazil using a time series of approximately 70 years. Neural network structures with two or more hidden layers showed a better result, minimizing the prediction error. |
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