Artificial neural network technique for rainfall forecasting applied to the São Paulo region
- Author
- VALVERDE RAMIREZ, Maria Cleofé1 ; FRAGA DE CAMPOS VELHO, Haroldo2 ; FERREIRA, Nelson Jesus1
[1] Centro de Previsão do Tempo e Estudos Climáticos (CPTEC), Instituto Nacional de Pesquisas Espaciais (INPE), Cachoiera Paulista, 12630-000 Sao Paulo, Brazil
[2] Laboratório de Computação e Matemática Aplicada (LAC), Instituto Nacional de Pesquisas Espaciais (INPE), P.O. Box 515, 12201-970 São José dos Campos (SP), Brazil - Source
Journal of hydrology (Amsterdam). 2005, Vol 301, Num 1-4, pp 146-162, 17 p ; Illustration , Table ; ref : 35 ref
- Publisher
- Elsevier Science, Amsterdam
- Publication country
- Netherlands
- Document type
- Article
- Language
- English
- Author keyword
- Artificial neural network Multiple linear regression Regional ETA model Statistical rainfall forecast
- Keyword (fr)
- Analyse statistique Coefficient corrélation Eau pluie Modèle Précipitation atmosphérique Prévision Réseau neuronal Brésil Sao Paulo Amérique du Sud
- Keyword (en)
- statistical analysis correlation coefficient rain water models atmospheric precipitation prediction neural networks Brazil Sao Paulo Brazil South America
- Keyword (es)
- Coeficiente correlación Agua llovediza Modelo Precipitación atmosférica Previsión Red neuronal Brasil America del sur
- Classification
- Pascal
- 001 Exact sciences and technology / 001E Earth, ocean, space / 001E01 Earth sciences / 001E01N Hydrology. Hydrogeology / 001E01N01 Hydrology
- Discipline
- Earth sciences
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 16385860
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.jhydrol.2004.06.028 
https://dx.doi.org/10.1016/j.jhydrol.2004.06.028
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