Autores
Garro Licón Beatriz Aurora
Sossa Azuela Juan Humberto
Vázquez Espinoza de los Monteros Roberto Antonio
Título Artificial neural network synthesis by means of artificial bee colony (ABC) algorithm
Tipo Congreso
Sub-tipo Memoria
Descripción 2011 IEEE Congress on Evolutionary Computation (CEC 2011)
Resumen Artificial bee colony (ABC) algorithm has been used in several optimization problems, including the optimization of synaptic weights from an Artificial Neural Network (ANN). However, this is not enough to generate a robust ANN. For that reason, some authors have proposed methodologies based on so-called metaheuristics that automatically allow designing an ANN, taking into account not only the optimization of the synaptic weights as well as the ANN's architecture, and the transfer function of each neuron. However, those methodologies do not generate a reduced design (synthesis) of the ANN. In this paper, we present an ABC based methodology, that maximizes its accuracy and minimizes the number of connections of an ANN by evolving at the same time the synaptic weights, the ANN's architecture and the transfer functions of each neuron. The methodology is tested with several pattern recognition problems.
Observaciones DOI: 10.1109/CEC.2011.5949637
Lugar New Orleans, LA
País Estados Unidos
No. de páginas 331-338
Vol. / Cap.
Inicio 2011-06-05
Fin 2011-06-08
ISBN/ISSN 978-1-4244-7834-7