@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 = "27 abr. 2024"
}