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Authors: César Daltoé Berci and Celso Pascoli Bottura

Affiliation: Universidade Estadual de Campinas, Brazil

Abstract: The use of genetic algorithms in ANNs training is not a new subject, several works have already accomplished good results, however not competitive with procedural methods for problems where the gradient of the error is well defined. The present document proposes an alternative for ANNs training using GA(Genetic Algorithms) to evolve the training process itself and not to evolve directly the network parameters. This way we get quite superior results and obtain a method competitive with these, usually used to training ANNs.

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Paper citation in several formats:
Berci, C. and Bottura, C. (2009). Evolving Gradient a New Approach to Perform Neural Network Training. In Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP; ISBN 978-989-674-002-3, SciTePress, pages 3-12. DOI: 10.5220/0002214000030012

@conference{workshop anniip09,
author={César Daltoé Berci. and Celso Pascoli Bottura.},
title={Evolving Gradient a New Approach to Perform Neural Network Training},
booktitle={Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP},
year={2009},
pages={3-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002214000030012},
isbn={978-989-674-002-3},
}

TY - CONF

JO - Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2009) - Workshop ANNIIP
TI - Evolving Gradient a New Approach to Perform Neural Network Training
SN - 978-989-674-002-3
AU - Berci, C.
AU - Bottura, C.
PY - 2009
SP - 3
EP - 12
DO - 10.5220/0002214000030012
PB - SciTePress