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dc.contributor.authorIreri, TG
dc.contributor.authorMurage, DK
dc.contributor.authorAbungu, NO
dc.date.accessioned2014-02-04T07:06:03Z
dc.date.available2014-02-04T07:06:03Z
dc.date.issued24-04-13
dc.identifier.citationIreri TG, Murage DK, Abungu NO. "Short Term Load Forecasting Using Artificial Neural Networks.". In: Mechanical Engineering Annual Conference. Juja; 2013.en_US
dc.identifier.urihttps://profiles.uonbi.ac.ke/abunguodero/publications/short-term-load-forecasting-using-artificial-neural-networks
dc.identifier.urihttp://hdl.handle.net/11295/64487
dc.description.abstractLoad forecasting refers to the prediction of future load conditions based on present or historical data. This is important especially for transmission planning and economic dispatch. In this paper, an Artificial Neural Network (ANN) is trained using historical data for a sub-station at Ruiru, Kenya and the corresponding loading conditions for the sub-station are used to test its accuracy in forecasting the electrical load when given other parameters.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.titleShort Term Load Forecasting Using Artificial Neural Networksen_US
dc.typePresentationen_US


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