@Article{SouzaVMSAKSWKJRDSMMGB:2016:NeNeAp,
               author = "Souza, Vitor Moura Cardoso e Silva and Vieira, Luis Eduardo 
                         Antunes and Medeiros, Cl{\'a}udia and Silva, L{\'{\i}}gia Alves 
                         da and Alves, Livia Ribeiro and Koga, Daiki and Sibeck, D. G. and 
                         Walsh, B. M. and Kanekal, S. G. and Jauer, P. R. and Rockenbach da 
                         Silva, Marlos and Dal Lago, Alisson and Silveira, Marcos Vinicius 
                         Dias and Marchezi, Jos{\'e} Paulo and Mendes, Odim and Gonzalez 
                         Alarcon, Walter Dem{\'e}trio and Baker, D. N.",
          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 {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {NASA Goddard Space Flight Center} and {Boston University} and 
                         {NASA Goddard Space Flight Center} 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 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {University of Colorado Boulder}",
                title = "A neural network approach for identifying particle pitch angle 
                         distributions in Van Allen Probes data",
              journal = "Space Weather",
                 year = "2016",
               volume = "14",
               number = "4",
                pages = "275--284",
                month = "Apr.",
             keywords = "pitch angle distributions, self-organizing maps, Van Allen belt's 
                         monitoring.",
             abstract = "Analysis of particle pitch angle distributions (PADs) has been 
                         used as a means to comprehend a multitude of different physical 
                         mechanisms that lead to flux variations in the Van Allen belts and 
                         also to particle precipitation into the upper atmosphere. In this 
                         work we developed a neural network-based data clustering 
                         methodology that automatically identifies distinct PAD types in an 
                         unsupervised way using particle flux data. One can promptly 
                         identify and locate three well-known PAD types in both time and 
                         radial distance, namely, 90° peaked, butterfly, and flattop 
                         distributions. In order to illustrate the applicability of our 
                         methodology, we used relativistic electron flux data from the 
                         whole month of November 2014, acquired from the Relativistic 
                         Electron-Proton Telescope instrument on board the Van Allen 
                         Probes, but it is emphasized that our approach can also be used 
                         with multiplatform spacecraft data. Our PAD classification results 
                         are in reasonably good agreement with those obtained by standard 
                         statistical fitting algorithms. The proposed methodology has a 
                         potential use for Van Allen belt's monitoring.",
                  doi = "10.1002/2015SW001349",
                  url = "http://dx.doi.org/10.1002/2015SW001349",
                 issn = "1542-7390",
             language = "en",
           targetfile = "souza_a neural.pdf",
        urlaccessdate = "28 abr. 2024"
}