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|Title:||Short-term load forecasting using wavelet networks||Authors:||Chang, C.S.
Power systems operation/planning
|Issue Date:||1998||Citation:||Chang, C.S.,Fu, W.,Yi, M. (1998). Short-term load forecasting using wavelet networks. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications 6 (4) : 217-223. ScholarBank@NUS Repository.||Abstract:||This paper describes an application of a type of neural network, called the wavelet network, to short-term load forecasting. Based on the wavelet transform theory, the recently developed wavelet network is proposed as an alternative to the feed-fonvard neural networks for approximating arbitrary nonlinear functions and for solving classification problems. Performance results are given for the daily peak and total load forecasting using data from a real power system. A comparison among results from the wavelet network, the radial-basis feedforward (RBF) neural network and back-propagation (BP) neural network shows that the wavelet network is encouraging.||Source Title:||International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications||URI:||http://scholarbank.nus.edu.sg/handle/10635/81157||ISSN:||09691170|
|Appears in Collections:||Staff Publications|
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