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@InProceedings{AraújoVelhGome:2012:MuOpEv,
               author = "Ara{\'u}jo, Amar{\'{\i}}sio da S. and Velho, Haroldo F. de 
                         Campos and Gomes, Vitor C. F.",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Multi-objective Optimization by an Evolutionary Algorithm for 
                         Calibrating an Hydrological Model",
                 year = "2012",
                pages = "456--464",
         organization = "International Symposium on Uncertainty Quantification and 
                         Stochastic Modeling, 1.",
             keywords = "parameter estimation, hydrological model, calibration, 
                         multi-objective optimization, pareto set.",
             abstract = "Hydrologic models simulate the river flow from the contributing 
                         basin for a given river. For the simulation process, the 
                         integration domain is discretized into computational cells. The 
                         inputs for such models are precipitation ratio and the initial 
                         flow. There are many parameters to be determined for an 
                         operational model, including the type of soil (porosity field, 
                         water flux between the bottom of the river and the water layer, 
                         among others). However, there is no unique set of parameters for 
                         representing the hydrology cycle. A multi-objective approach is 
                         employed to address the problem. The Pareto set is calculated for 
                         the IPH2 model by an epidemic genetic algorithm.",
  conference-location = "S{\~a}o Sebasti{\~a}o, SP",
      conference-year = "Feb. 26th to Mar. 2nd",
                 issn = "2238-1007",
           targetfile = "67_ArtigoEngl_Final.pdf",
        urlaccessdate = "17 jan. 2021"
}


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