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@InProceedings{NowosadCampRios:2000:NeNeNe,
               author = "Nowosad, A. G. and Campos Velho, H. F. de and Rios Neto, A.",
          affiliation = "{INPE-Sao Jose dos Campos-12227-010-SP-Brasil}",
                title = "Neural network as a new approach for data assimilation",
            booktitle = "Anais...",
                 year = "2000",
                pages = "3078--3086",
         organization = "Congresso Brasileiro de Meteorologia, 11.",
             keywords = "data assimilation, neural networks, Kalman filter, nonlinear 
                         dynamics.",
             abstract = "Multilayer Perceptron Neural Networks are tested as a new method 
                         for data assimilation in DYNAMO meteorological model. The approach 
                         {"}emulates{"} the Kalman Filter data assimilation method avoiding 
                         recalculation of the gain matrix at each instant of assimilation. 
                         A new prodedure for training the networks is also presented, based 
                         on a modification in the backpropagation algorithm. An Adaptive 
                         Extended Kalman Filter was used to provide examples for network 
                         training.",
  conference-location = "Rio de Janeiro",
      conference-year = "16-20 out. 2000",
           copyholder = "SID/SCD",
             language = "pt",
         organisation = "SBMET",
           targetfile = "PT00002.PDF",
        urlaccessdate = "28 mar. 2024"
}


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