# PROBLEMS AND FEATURES OF EVOLUTIONARY ALGORITHMS TO BUILD HYBRID TRAINING METHODS FOR RECURRENT NEURAL NETWORKS

### M. P. Cuéllar, M. Delgado, M. C. Pegalajar

#### 2007

#### Abstract

Dynamical recurrent neural networks are models suitable to solve problems where the input and output data may have dependencies in time, like grammatical inference or time series prediction. However, traditional training algorithms for these networks sometimes provide unsuitable results because of the vanishing gradient problems. This work focuses on hybrid proposals of training algorithms for this type of neural networks. The methods studied are based on the combination of heuristic procedures with gradient-based algorithms. In the experimental section, we show the advantages and disadvantages that we may find when using these training techniques in time series prediction problems, and provide a general discussion about the problems and cases of different hybridations based on genetic evolutionary algorithms.

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#### Paper Citation

#### in Harvard Style

P. Cuéllar M., Delgado M. and C. Pegalajar M. (2007). **PROBLEMS AND FEATURES OF EVOLUTIONARY ALGORITHMS TO BUILD HYBRID TRAINING METHODS FOR RECURRENT NEURAL NETWORKS** . In *Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,* ISBN 978-972-8865-89-4, pages 204-211. DOI: 10.5220/0002383502040211

#### in Bibtex Style

@conference{iceis07,

author={M. P. Cuéllar and M. Delgado and M. C. Pegalajar},

title={PROBLEMS AND FEATURES OF EVOLUTIONARY ALGORITHMS TO BUILD HYBRID TRAINING METHODS FOR RECURRENT NEURAL NETWORKS},

booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},

year={2007},

pages={204-211},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0002383502040211},

isbn={978-972-8865-89-4},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,

TI - PROBLEMS AND FEATURES OF EVOLUTIONARY ALGORITHMS TO BUILD HYBRID TRAINING METHODS FOR RECURRENT NEURAL NETWORKS

SN - 978-972-8865-89-4

AU - P. Cuéllar M.

AU - Delgado M.

AU - C. Pegalajar M.

PY - 2007

SP - 204

EP - 211

DO - 10.5220/0002383502040211