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• W2324975932 abstract "The management of the demand and supply pattern of electrical energy in Nigeria is a complex task that requires highly informative approaches; these approaches should be able to provide adequate models for predicting the future utilization of the energy in order to boost the economy of the nation. This study applied an Artificial Neural Network-based model, often called Radial Basis Function (RBF) network to time-series prediction of electricity consumption in Nigerian using historical data gathered from CBN annual bulletins. The implementation of the model was carried out using Neural Network Tool (nntool) of the MATLAB 7.6.0 (R2008a) tool box. The study showed that RBF network performs better than its equivalent Backpropagation (BP) networks that were compared with it. KeywordPrediction; Radial Basis Function (RBF) Network; MATLAB; Electricity Consumption; Nigeria" @default.
• W2324975932 created "2016-06-24" @default.
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• W2324975932 date "2014-06-27" @default.
• W2324975932 modified "2023-09-27" @default.
• W2324975932 title "Predicting Electricity Consumption Using Radial Basis Function (RBF) Network" @default.
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• W2324975932 doi "https://doi.org/10.5963/ijcsai0402004" @default.
• W2324975932 hasPublicationYear "2014" @default.
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