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

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15 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 languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Pages1365-1370
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2005
EventInternational Joint Conference on Neural Networks, IJCNN 2005 - Montreal, QC, Canada
Duration: 31 Jul 20054 Aug 2005

Conference

ConferenceInternational Joint Conference on Neural Networks, IJCNN 2005
Country/TerritoryCanada
CityMontreal, QC
Period31/07/054/08/05

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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