Genetic algorithm-based variable translation wavelet neural network and its application

S. H. Ling; Hung Fat Frank Leung

doi:10.1109/IJCNN.2005.1556073

Genetic algorithm-based variable translation wavelet neural network and its application

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

16 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Pages	1365-1370
Number of pages	6
DOIs	https://doi.org/10.1109/IJCNN.2005.1556073
Publication status	Published - 1 Dec 2005
Event	International Joint Conference on Neural Networks, IJCNN 2005 - Montreal, QC, Canada Duration: 31 Jul 2005 → 4 Aug 2005

Conference

Conference	International Joint Conference on Neural Networks, IJCNN 2005
Country/Territory	Canada
City	Montreal, QC
Period	31/07/05 → 4/08/05

ASJC Scopus subject areas

Software
Artificial Intelligence

More information

10.1109/IJCNN.2005.1556073

http://hdl.handle.net/10397/1375

Cite this

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title = "Genetic algorithm-based variable translation wavelet neural network and its application",

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.",

author = "Ling, {S. H.} and Leung, {Hung Fat Frank}",

year = "2005",

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doi = "10.1109/IJCNN.2005.1556073",

language = "English",

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Genetic algorithm-based variable translation wavelet neural network and its application. / Ling, S. H.; Leung, Hung Fat Frank.

Proceedings of the International Joint Conference on Neural Networks. 2005. p. 1365-1370 1556073.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - 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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M3 - Conference article published in proceeding or book

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T2 - International Joint Conference on Neural Networks, IJCNN 2005

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Genetic algorithm-based variable translation wavelet neural network and its application

Abstract

Conference

ASJC Scopus subject areas

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