@InProceedings{FurtadoCampMaca:2012:DaAsNe,
               author = "Furtado, Helaine C. M. and Campos Velho, Haroldo F. de and Macau, 
                         Elbert E. N.",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Data assimilation by neural network emulating representer method 
                         applied to the wave equation",
            booktitle = "Proceedings...",
                 year = "2012",
                pages = "476--484",
         organization = "International Symposium on Uncertainty Quantification and 
                         Stochastic Modeling, 1.",
             keywords = "data assimilation, neural network, variational method, representer 
                         method, wave equation.",
             abstract = "Description of a physical phenomenon through differential 
                         equations has errors involved, since the mathematical model is 
                         always an approximation of reality. For an operational prediction 
                         system, one strategy to deal with uncertainties from the modeling 
                         and observation errors is to add some information from the real 
                         dynamics into mathematical model. This aditional information 
                         consists of observations on the phenomenon. However, the 
                         observational data insertion should be done carefully, for 
                         avoiding a worse performance of the prediction. Technical data 
                         assimilation are tools to combine data from physical-mathematics 
                         model with observational data to obtain a better forecast. Two 
                         data assimilation methods are compared here: the Kalman Filter 
                         method, and artificial neural network. Artificial neural networks 
                         appear as a novel method in the context for data assimilation. The 
                         performance of the methods is evaluated under application to wave 
                         propagation model (Bennet,2002).",
  conference-location = "S{\~a}o Sebasti{\~a}o, SP",
      conference-year = "Feb. 26th to Mar. 2nd, 2012",
                 issn = "2238-1007",
           targetfile = "71-Helaine.pdf",
        urlaccessdate = "29 jun. 2024"
}