@InProceedings{FurtadoCintCampHart:2006:DiScDa,
               author = "Furtado, H. C. M. and Cintra, Ros{\^a}ngela Saher Corr{\^e}a and 
                         Campos Velho, Haroldo Fraga de and Harter, Fabr{\'{\i}}cio 
                         Pereira",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Different Schemes for Data Assimilation for the Lorenz Dynamical 
                         System",
            booktitle = "Anais...",
                 year = "2006",
         organization = "Congresso Nacional de Matem{\'a}tica Aplicada e Computacional, 
                         29. (CNMAC).",
             abstract = "Data assimilation is a step for improving forecasting process by 
                         means of a weighted combination between observational and data 
                         from a mathetical model. This procedure is essential for 
                         operational prediction centers for weather, ocean circulation, and 
                         atmospheric pollution. The goal here is to compare four schemes 
                         for data assimilation: Kalman filter [1, 2, 4, 5], optimal 
                         interpolation [1, 2, 4], variational approach [1, 2, 4], and 
                         artificial neural networks (ANN) [3, 5]. The multilayer perceptron 
                         is the approach used to implement the ANN. The assimilation 
                         techniques are tested on the Lorenz dynamical system. It is 
                         imorportant to note that ANN is a method recently developed, and 
                         its application is under study. However, all thecniques tested 
                         presented a good performance, depending on the ratio of sampling 
                         of the observations. From computational point of view, the ANN 
                         presented a best perfoamance, considering only a trained ANN.",
  conference-location = "Campinas",
      conference-year = "18-21 set.",
             language = "pt",
         organisation = "SBMAC",
        urlaccessdate = "15 jan. 2021"
}