Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data.

Magar, Rajendra

dc.contributor.author	Magar, Rajendra
dc.date.accessioned	2014-03-21T10:14:56Z
dc.date.available	2014-03-21T10:14:56Z
dc.date.issued	2012
dc.identifier.citation	Pages 15.	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/860
dc.description.abstract	Reservoir inflow forecast is a key component in planning development, design, operation and maintenance of the available water resources. Inflow forecast models are useful in many water resources applications such as flood control, drought management, optimal reservoir operation, hydropower generation (Yeh, 1985).	en_US
dc.language.iso	en_US	en_US
dc.publisher	Journal of Hydrology	en_US
dc.subject	Staff Publication - SoET	en_US
dc.subject	Staff Publication - CE
dc.title	Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data.	en_US
dc.type	Article	en_US