Predicting the Water Inflow Into the Dam Reservoir Using the Hybrid Intelligent GP-ANN- NSGA-II Method

A key issue for effective management and operating of dam reservoirs is predicting the water inflow values into dam reservoir. To address this subject, here, genetic programming (GP) is used by proposing two cases. In the first case, water inflow values are predicted separately for each month. Howev...

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Veröffentlicht in:	Water resources management Jg. 38; H. 11; S. 4137 - 4159
Hauptverfasser:	Moeini, Ramtin, Nasiri, Kamran, Hosseini, Seyed Hossein
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.09.2024 Springer Nature B.V
Schlagworte:	Algorithms Atmospheric Sciences Case studies Civil Engineering Correlation coefficient Correlation coefficients Dams data collection Datasets Earth and Environmental Science Earth Sciences Environment Genetic algorithms Geotechnical Engineering & Applied Earth Sciences hybrids Hydrogeology Hydrology/Water Resources Inflow Methods Neural networks Reservoirs Root-mean-square errors Variables water Water inflow Water resources Water inflow prediction NSGA-II algorithm Artificial neural network Zayandehroud dam Genetic programming
ISSN:	0920-4741, 1573-1650
Online-Zugang:	Volltext
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