Sampling/stochastic dynamic programming for optimal operation of multi-purpose reservoirs using artificial neural network-based ensemble streamﬂow predictions

Due to limited water resources and the increasing demand for agricultural products, it is significantly important to operate surface water reservoirs optimally, especially those located in arid and semi-arid regions. This paper investigates uncertainty-based optimal operation of a multi-purpose wate...

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Vydáno v:	Journal of hydroinformatics Ročník 16; číslo 4; s. 907 - 921
Hlavní autoři:	Anvari, Sedigheh, Mousavi, S. Jamshid, Morid, Saeed
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London IWA Publishing 01.01.2014
Témata:	Agricultural products Arid zones Artificial neural networks Case studies Computer simulation Dynamic programming Earth sciences Earth, ocean, space Exact sciences and technology Hydrology Hydrology. Hydrogeology Inflow Mathematical models Multipurpose reservoirs Neural networks Optimization Policies Real time operation Reservoir operation Reservoirs Sampling Semi arid areas Semiarid zones Stream discharge Stream flow Surface water Water inflow Water reservoirs Water resources Middle East Iran Asia models water policy neural networks reservoirs arid environment digital simulation case studies classification surface water water resources stochastic models optimization water resource management prediction uncertainties streamflow
ISSN:	1464-7141, 1465-1734
On-line přístup:	Získat plný text
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