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https://doi.org/10.5194/hess-10-289-2006
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the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hess-10-289-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?
Y. Tang
Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
P. Reed
Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
T. Wagener
Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
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125 citations as recorded by crossref.
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- Parameter identification and calibration of the Xin’anjiang model using the surrogate modeling approach Y. Ye et al. 10.1007/s11707-014-0424-0
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- Incorporating multiple observations for distributed hydrologic model calibration: An approach using a multi-objective evolutionary algorithm and clustering S. Khu et al. 10.1016/j.advwatres.2008.07.011
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- Development of an Automatic Calibration Tool Using Genetic Algorithm for the ARNO Conceptual Rainfall-Runoff Model M. Khazaei et al. 10.1007/s13369-013-0903-8
- Pareto-Optimal Multi-objective Inversion of Geophysical Data S. Schnaidt et al. 10.1007/s00024-018-1784-2
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