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@Article{HärterCampRempChia:2008:NeNeAu,
               author = "H{\"a}rter, Fabr{\'{\i}}cio Pereira and Campos Velho, Haroldo 
                         Fraga de and Rempel, {\'E}rico Luiz and Chian, Abraham Chian 
                         Long",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Tecnol{\'o}gico de Aeron{\'a}utica} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Neural networks in auroral data assimilation",
              journal = "Journal of Atmospheric and Solar-Terrestrial Physics",
                 year = "2008",
               volume = "70",
               number = "10",
                pages = "1243--1250",
                month = "July",
             keywords = "Auroral radio emissions, Nonlinear dynamics, Chaos, Data 
                         assimilation, Kalman filter, Neural networks.",
             abstract = "Data assimilation is an essential step for improving space weather 
                         forecasting by means of a weighted combination between 
                         observational data and data from a mathematical model. In the 
                         present work data assimilation methods based on Kalman filter (KF) 
                         and artificial neural networks are applied to a three-wave model 
                         of auroral radio emissions. A novel data assimilation method is 
                         presented, whereby a multilayer perceptron neural network is 
                         trained to emulate a KF for data assimilation by using 
                         cross-validation. The results obtained render support for the use 
                         of neural networks as an assimilation technique for space weather 
                         prediction.",
                  doi = "10.1016/j.jastp.2008.03.018",
                  url = "http://dx.doi.org/10.1016/j.jastp.2008.03.018",
                 issn = "1364-6826",
             language = "en",
           targetfile = "neural.pdf",
        urlaccessdate = "15 jan. 2021"
}


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