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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1357

Title: A genetic algorithm based neural-tuned neural network
Authors: Ling, S. H.
Lam, H. K.
Leung, Frank H. F.
Lee, Y. S.
Subjects: Genetic algorithm
Neural network
Pattern recognition
Sunspot forecasting
Issue Date: 2003
Publisher: IEEE
Citation: IECON'03 : the 29th annual conference of the IEEE Industrial Electronics Society : Roanoke, Virginia, USA, November 2nd (Sunday) to Thursday, November 6th (Thursday) 2003, p. 2423-2428.
Abstract: This paper presents a neural-tuned neural network, which is trained by genetic algorithm (GA). The neural-tuned neural network consists of a neural network and a modified neural network. In the modified neural network, a neuron model with two activation functions is introduced. Some parameters of these activation functions will be tuned by neural network. The proposed network structure can increase the search space of the network and gives better performance than traditional feed-forward neural networks. Some application examples are given to illustrate the merits of the proposed network.
Rights: © 2003 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.
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.
Type: Conference Paper
URI: http://hdl.handle.net/10397/1357
ISBN: 0-7803-7906-3
Appears in Collections:EIE Conference Papers & Presentations

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