@InProceedings{SambattiGoFuLuVeCh:2014:DeInCo,
               author = "Sambatti, Sabrina Bergoch Monteiro and Gomes, Vitor Conrado Faria 
                         and Furtado, Helaine C. M. and Luz, Eduardo F. P. and Velho, 
                         Haroldo Fraga de Campos and Char{\~a}o, Andrea Schwertner",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade Federal de Santa Maria (UFSM)}",
                title = "Determining Initial Condition by FPGA",
            booktitle = "Proceedings...",
                 year = "2014",
         organization = "Uncertainties.",
             keywords = "FPGA, Data Assimilation, MPCA, Neural Network.",
             abstract = "Data assimilation is a mathematical tool to compute an appropriate 
                         combination between observation and data from a mathematical model 
                         in order to determine the best initial condition. Advanced methods 
                         are Extended Kalman Filter (EKF), and three and four dimensional 
                         variation methods (3D-Var, 4D-Var) employed to perform data 
                         assimilation. Artificial neural networks can also be applied, once 
                         it is able to emulate the EKF or 3D/4D-Var procedures, reducing 
                         the computational complexity. The supervised Multilayer Perceptron 
                         Artificial Neural Network (MLP-ANN) is used here to emulate the 
                         Kalman filter. The MLP-ANN is implemented in a reconfigurable 
                         hybrid system: FPGA (Field-Programmable Gate Array). The linear 1D 
                         wave equation is the dynamic system used for testing the 
                         framework. Good performance was obtained with neural network 
                         emulating the Kalman filter. The neural network is automatically 
                         configured using the meta-heuristic Multi-Particle Collision 
                         Algorithm (MPCA).",
  conference-location = "Rouen",
      conference-year = "2014",
                label = "lattes: 8584137507032098 1 SambattiGomeVelhChar:2014:DeInCo",
             language = "en",
           targetfile = "Sambatti_Determining.pdf",
        urlaccessdate = "27 abr. 2024"
}