@InProceedings{AnochiSambLuzCamp:2013:MPMeAp,
               author = "Anochi, Juliana A and Sambatti, Sabrina B and Luz, Eduardo 
                         F{\'a}vero Pacheco da and Campos Velho, Haroldo Fraga de",
          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)}",
                title = "New learning strategy for supervised neural network: MPCA 
                         meta-heuristic approach",
            booktitle = "Anais...",
                 year = "2013",
                pages = "01--06",
         organization = "Congresso Brasileiro de Intelig{\^e}ncia Computacional, (CBIC).",
            publisher = "Sociedade Brasileira de Intelig{\^e}ncia Computacional",
             keywords = "Artificial neural network, Learning process, MPCA: multi-particle 
                         collision algorithm, Sasonal precipitacion climate prediction.",
             abstract = "The problem of parameter optimization for a feed- forward 
                         artificial neural network (ANN) to determined its best 
                         architecture is addressed. A new metaheuristic called Multiple 
                         Particle Collision Algorithm (MPCA), introduced by Luz et al. 
                         [12], was applied to design an optimum architecture for two models 
                         of supervised neural network: the Multilayer Perceptron (MLP), and 
                         recurrent Elman network. The NN obtained using this approach is 
                         said to be self-configurable. In addition, two strategies are 
                         employed for calculating the connection weights to the MLP and 
                         Elman networks: MPCA, and backpropagation algorithm. The resulting 
                         ANNs were applied to predict the monthly mesoscale climate for the 
                         precipitation field. The com- parison is performed between the ANN 
                         configuration obtained by automatic process and another 
                         configuration proposed by a human specialist.",
  conference-location = "Recife Natal (RN), Brasil",
      conference-year = "2013",
                label = "lattes: 5142426481528206 4 AnochiSambLuzCamp:2013:MPMeAp",
             language = "en",
                  url = "http://brics-cci.org/technical-program-of-cbic/",
               volume = "01",
        urlaccessdate = "12 maio 2024"
}