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@InProceedings{NowosadCampRios:2000:NeNeDa,
               author = "Nowosad, Alexandre Guirland and Campos Velho, Haroldo Fraga de and 
                         Rios Neto, Atair",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade do Vale 
                         do Para{\'{\i}}ba (UNIVAP)}",
                title = "Neural Networks in Data Assimilation",
            booktitle = "Abstracts...",
                 year = "2000",
                pages = "8",
         organization = "Encontro Regional De Matem{\'a}tica Aplicada e Computacional 
                         (ERMAC).",
             keywords = "Neural networks, Data assimilation, Computer science, 
                         ENGINEERING.",
             abstract = "ABSTRACT: In the case of atmospheric continuous data assimilation 
                         there are many deterministic and probabilistic methods. A new 
                         approach based on neural networks is proposed. The new aproach 
                         adopted requires training of a multilayered perceptron to emulate 
                         a chosen data assimlation method. Here, Kalman filter data 
                         assimilation methods were used to generate training examples for 
                         the networks. Tests are performed using the Henon mapping and 
                         Lorenz evolution system. In the case of Henon system an Adaptive 
                         Extended Kalman Filter is used to provide examples for network 
                         training. In the case of Lorenz system the Extended Kalman Filter 
                         is used for network training. The preliminary results obtained are 
                         promising. .",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP",
      conference-year = "15-17 mar.",
             language = "en",
        urlaccessdate = "24 jan. 2021"
}


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