DSpace
 

KNUSTSpace >
Journal of Science and Technology (JUST) >
Journal of Science and Technology 2000- >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/4995

Title: Monthly energy consumption forecasting using Wavelet analysis and radial basis function neural network
Authors: Frimpong, E. A.
Okyere, P. Y.
Keywords: Load forecasting
artificial neural network
radial basis function
wavelet transform
Issue Date: 2010
Publisher: Journal of Science and Technology
Citation: Journal of Science and Technology, Vol. 30, No. 2 (2010), pp 157 - 164
Abstract: Monthly energy forecasts help heavy consumers of electric power to prepare adequate budget to pay their electricity bills and also draw the attention of management and stakeholders to electricity consumption levels so that energy efficiency measures are put in place to reduce cost. In this paper, a wavelet transform and radial basis function neural network based energy forecast model is developed to predict monthly energy consumption. The model was developed using the monthly energy consumption of Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana for a 9-year period. A mean absolute percentage error of 7.94% was achieved when the forecast model was tested over a 60-month period.
Description: Article published in the Journal of Science and Technology, Vol. 30, No. 2 (2010), pp 157- 164
URI: http://hdl.handle.net/123456789/4995
Appears in Collections:Journal of Science and Technology 2000-

Files in This Item:

File Description SizeFormat
Frimpong.pdf244.5 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback