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International Journal of

Recent Trends in Engineering

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International Journal of Recent Trends in Engineering (IJRTE)

ISSN 1797-9617

Volume 1, Number 2, May 2009

Issue on Computer Science

Page(s): 84-89

Design of Genetically Evolved Artificial Neural Network Using Enhanced Genetic Algorithm

M. NirmalaDevi, N. Mohankumar, M. Karthick, Nikhil Jayan, R. Nithya, S. Shobana, M. Shyam Sundar and S. Arumugam

Full text: PDF

Abstract

This paper deals with designing an Artificial Neural Network (ANN) whose weights are genetically evolved using the proposed Enhanced Genetic Algorithm (EGA), thereby obtaining optimal weight set. The performance is analysed by fitness function based ranking. The ability of learning may depend on many factors like the number of neurons in the hidden layer, number of training input patterns and the type of activation function used. By varying each parameter, the performance of the proposed EGA algorithm is compared with normal NN training. The results show that the proposed algorithm is better in terms of error convergence.

Index Terms

ANN,EGA,GAs

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