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Simultaneous Evolution of Architecture and Connection Weights in Artificial Neural Network

by G. V. R. Sagar, S. Venkata Chalam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 4
Year of Publication: 2012
Authors: G. V. R. Sagar, S. Venkata Chalam
10.5120/8410-2047

G. V. R. Sagar, S. Venkata Chalam . Simultaneous Evolution of Architecture and Connection Weights in Artificial Neural Network. International Journal of Computer Applications. 53, 4 ( September 2012), 23-28. DOI=10.5120/8410-2047

@article{ 10.5120/8410-2047,
author = { G. V. R. Sagar, S. Venkata Chalam },
title = { Simultaneous Evolution of Architecture and Connection Weights in Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 4 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 23-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number4/8410-2047/ },
doi = { 10.5120/8410-2047 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:53:16.809431+05:30
%A G. V. R. Sagar
%A S. Venkata Chalam
%T Simultaneous Evolution of Architecture and Connection Weights in Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 4
%P 23-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The important issue for Designing architecture isthe evolution of Artificial Neural Network (ANN). There is no systematic method to design a near-optimal architecture for a given application or task. The pattern classification methods are used to design the neural network architectures and efforts towards the automatic design of network topologies, constructive and destructive algorithms can be used. In the proposed work the optimization of architectures and connection weights uses the evolutionary process. A single-point crossover is applied with selective schemas on the network space and evolution is introduced in the mutation stage so that an optimized ANNs are achieved.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial neural network topology mutation schema theory

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