Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/1375
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electronic and Information Engineering | - |
dc.creator | Ling, SH | - |
dc.creator | Leung, FHF | - |
dc.date.accessioned | 2014-12-11T08:26:23Z | - |
dc.date.available | 2014-12-11T08:26:23Z | - |
dc.identifier.isbn | 0-7803-9048-2 | - |
dc.identifier.uri | http://hdl.handle.net/10397/1375 | - |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.rights | © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | en_US |
dc.rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | en_US |
dc.subject | Electric load forecasting | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Parameter estimation | en_US |
dc.title | Genetic algorithm-based variable translation wavelet neural network and its application | en_US |
dc.type | Conference Paper | en_US |
dc.description.otherinformation | Author name used in this publication: F. H. F. Leung | en_US |
dc.description.otherinformation | "Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering" | en_US |
dc.description.otherinformation | Refereed conference paper | en_US |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | 2005 IEEE International Joint Conference on Neural Networks (IJCNN) : Montreal, QC, Canada, July 31-August 4, 2005, p. 1365-1370 | - |
dcterms.issued | 2005 | - |
dc.identifier.isi | WOS:000235178002006 | - |
dc.identifier.scopus | 2-s2.0-33750141680 | - |
dc.identifier.rosgroupid | r25791 | - |
dc.description.ros | 2005-2006 > Academic research: refereed > Refereed conference paper | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | VoR allowed | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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Algorithm-based variable translation_05.pdf | 896.09 kB | Adobe PDF | View/Open |
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