Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1375
Title: Genetic algorithm-based variable translation wavelet neural network and its application
Authors: Ling, S. H.
Leung, Frank H. F.
Subjects: Electric load forecasting
Genetic algorithms
Parameter estimation
Issue Date: 2005
Publisher: IEEE
Source: 2005 IEEE International Joint Conference on Neural Networks (IJCNN) : Montreal, QC, Canada, July 31-August 4, 2005, p. 1365-1370.
Abstract: A variable translation wavelet neural network (VTWNN) trained by genetic algorithm is presented in this paper. In the proposed wavelet neural network, the translation parameters are variables depending on the network inputs. Thanks to the variable translation parameter, the network becomes an adaptive one, providing better performance and increased learning ability than conventional wavelet neural networks. Genetic algorithm is applied to train the parameters of the proposed wavelet neural network. An application example on short-term daily electric load forecasting in Hong Kong is presented to show the merits of the proposed network.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1375
ISBN: 0-7803-9048-2
Appears in Collections:EIE Conference Papers & Presentations

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