@Article{WeigangSaGalvBevi:1998:PrLePa,
               author = "Weigang, Li and Sa, Leonardo Deane de Abreu and Galvao, Geraldo 
                         Pereira and Bevilaqua, Rute Maria",
                title = "Prediction of the level of Paraguay river using neural networks",
              journal = "Pesquisa Agropecu{\'a}ria Brasileira",
                 year = "1998",
               volume = "33",
               number = "Numero Especial",
                pages = "1791--1797",
                month = "out.",
             keywords = "ESTUDO DO SINAL GEOFISICA, RIO PARAGUAI (MS), REDES NEURAIS.",
             abstract = "Backpropagation neural networks are implemented for prediction of 
                         the level of Paraguay River at Ladario city, MS. Using 274 monthly 
                         mean values, the trained network predicts the levels of the four 
                         next months with relative errors smaller than 17. For some special 
                         points, the prediction results also show that the neural network 
                         method seems to be usefull to predict time series related to 
                         phenomena influenced by complex climatic and geophysical 
                         processes, and it does not deal directly with causal relationships 
                         involved in the phenomena studied. A discussion about the 
                         variability of the estimation errors for different predicted data 
                         is carried out here.",
                 issn = "0100-204X",
                label = "8316",
           targetfile = "084-pant.p65 - 084-pant.pdf",
        urlaccessdate = "16 jun. 2024"
}