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Revista Facultad de Ingeniería Universidad de Antioquia
versión impresa ISSN 0120-6230versión On-line ISSN 2422-2844
Resumen
TABARES, Héctor; BRANCH, John y VALENCIA, Jaime. Dynamic topology generation of an artificial neural network of the multilayer perceptron type. Rev.fac.ing.univ. Antioquia [online]. 2006, n.38, pp.146-162. ISSN 0120-6230.
This paper deals with an approximate constructive method to find architectures of artificial neuronal network (ANN) of the type MultiLayer Percetron (MLP) which solves a particular problem. This method is supplemented with the technique of the Forced search of better local minima. The training of the net uses an algorithm basic descending gradient (BDG). Techniques such as repetition of the training and the early stopping (cross validation) are used to improve the results. The evaluation approach is based not only on the learning abilities but also on the generalization of the specific generated architectures of a domain. Experimental results are presented in order to prove the effectiveness of the proposed method. These are compared with architectures found by other methods.
Palabras clave : Artificial Neural Networks; Multi-layer Perceptron; Topology; Architecture.