A Genetic Algorithm Based Neural-Tuned Neural Network

S. H. Ling; H. K. Lam; Hung Fat Frank Leung; Y. S. Lee

doi:10.1109/IECON.2003.1280624

A Genetic Algorithm Based Neural-Tuned Neural Network

S. H. Ling, H. K. Lam, Hung Fat Frank Leung, Y. S. Lee

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

5 Citations (Scopus)

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.

Original language	English
Title of host publication	IECON Proceedings (Industrial Electronics Conference)
Pages	2423-2428
Number of pages	6
DOIs	https://doi.org/10.1109/IECON.2003.1280624
Publication status	Published - 1 Dec 2003
Event	The 29th Annual Conference of the IEEE Industrial Electronics Society - Roanoke, VA, United States Duration: 2 Nov 2003 → 6 Nov 2003

Conference

Conference	The 29th Annual Conference of the IEEE Industrial Electronics Society
Country/Territory	United States
City	Roanoke, VA
Period	2/11/03 → 6/11/03

Keywords

Genetic Algorithm
Neural Network
Pattern Recognition
Sunspot Forecasting

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

More information

10.1109/IECON.2003.1280624

http://hdl.handle.net/10397/1357

Cite this

@inproceedings{a084480409664379bf0f0f114bc65bda,

title = "A Genetic Algorithm Based Neural-Tuned Neural Network",

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.",

keywords = "Genetic Algorithm, Neural Network, Pattern Recognition, Sunspot Forecasting",

author = "Ling, {S. H.} and Lam, {H. K.} and Leung, {Hung Fat Frank} and Lee, {Y. S.}",

year = "2003",

month = dec,

day = "1",

doi = "10.1109/IECON.2003.1280624",

language = "English",

pages = "2423--2428",

booktitle = "IECON Proceedings (Industrial Electronics Conference)",

note = "The 29th Annual Conference of the IEEE Industrial Electronics Society ; Conference date: 02-11-2003 Through 06-11-2003",

}

TY - GEN

T1 - A Genetic Algorithm Based Neural-Tuned Neural Network

AU - Ling, S. H.

AU - Lam, H. K.

AU - Leung, Hung Fat Frank

AU - Lee, Y. S.

PY - 2003/12/1

Y1 - 2003/12/1

N2 - 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.

AB - 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.

KW - Genetic Algorithm

KW - Neural Network

KW - Pattern Recognition

KW - Sunspot Forecasting

UR - http://www.scopus.com/inward/record.url?scp=1442358131&partnerID=8YFLogxK

U2 - 10.1109/IECON.2003.1280624

DO - 10.1109/IECON.2003.1280624

M3 - Conference article published in proceeding or book

SP - 2423

EP - 2428

BT - IECON Proceedings (Industrial Electronics Conference)

T2 - The 29th Annual Conference of the IEEE Industrial Electronics Society

Y2 - 2 November 2003 through 6 November 2003

ER -

A Genetic Algorithm Based Neural-Tuned Neural Network

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this