Multi-objective optimization of empirical hydrological model for streamflow prediction

•The MODE-ACM algorithm is firstly introduced for parameter estimation of hydrologic model.•We propose an enhanced Pareto multi-objective differential algorithm EPMODE.•The performance of EPMODE and MODE-ACM is tested on five benchmark problems.•EPMODE and MODE-ACM are further applied to an artifici...

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Vydané v:	Journal of hydrology (Amsterdam) Ročník 511; s. 242 - 253
Hlavní autori:	Guo, Jun, Zhou, Jianzhong, Lu, Jiazheng, Zou, Qiang, Zhang, Huajie, Bi, Sheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 16.04.2014
Predmet:	Algorithms Calibration case studies Effectiveness Empirical analysis Evolutionary algorithms hydrologic models Hydrological model Hydrology Mathematical models Model calibration Multi-objective optimization Optimization Pareto optimality prediction stream flow Streamflow forecasting Multi-objective optimization Streamflow forecasting Model calibration Hydrological model
ISSN:	0022-1694, 1879-2707
On-line prístup:	Získať plný text
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