A COMPARATIVE STUDY OF EVOLUTIONARY ALGORITHMS FOR TRAINING ELMAN RECURRENT NEURAL NETWORKS TO PREDICT AUTONOMOUS INDEBTEDNESS

Cuéllar M.P., Navarro A., Pegalajar M.C, Pérez-Pérez R.

Abstract

This paper presents a training model for Elman recurrent neural networks, based on evolutionary algorithms. The proposed evolutionary algorithms are classic genetic algorithms, the multimodal clearing algorithm and the CHC algorithm. These training algorithms are compared in order to assess the effectiveness of each training model when predicting Spanish autonomous indebtedness.

References

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Paper Citation


in Harvard Style

M.P. C., A. N., M.C P. and R. P. (2004). A COMPARATIVE STUDY OF EVOLUTIONARY ALGORITHMS FOR TRAINING ELMAN RECURRENT NEURAL NETWORKS TO PREDICT AUTONOMOUS INDEBTEDNESS . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 972-8865-00-7, pages 461-464. DOI: 10.5220/0002629204610464


in Bibtex Style

@conference{iceis04,
author={Cuéllar M.P. and Navarro A. and Pegalajar M.C and Pérez-Pérez R.},
title={A COMPARATIVE STUDY OF EVOLUTIONARY ALGORITHMS FOR TRAINING ELMAN RECURRENT NEURAL NETWORKS TO PREDICT AUTONOMOUS INDEBTEDNESS},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2004},
pages={461-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002629204610464},
isbn={972-8865-00-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A COMPARATIVE STUDY OF EVOLUTIONARY ALGORITHMS FOR TRAINING ELMAN RECURRENT NEURAL NETWORKS TO PREDICT AUTONOMOUS INDEBTEDNESS
SN - 972-8865-00-7
AU - M.P. C.
AU - A. N.
AU - M.C P.
AU - R. P.
PY - 2004
SP - 461
EP - 464
DO - 10.5220/0002629204610464