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Autores:
Daniel Rivero, Julián Dorado, Juan Ramón Rabuñal, Marcos Gestal
Título: A Comparison Between ANN Generation and Training Methods and Their Development by Means of Graph Evolution: 2 Sample Problems
Congreso: 9th International Work-Conference on Artificial Neural Networks (IWANN 2007)
Lugar Celebración: Heidelberg, Berlin
Fecha Celebración: 20-22 de Junio de 2007
Publicación: Lecture Notes in Computer Science. Computational and Ambient Intelligence
ISBN: 3-540-73006-0
Volumen: LNCS 4507
Páginas: 94-101
Editorial: Springer-Verlag
Fecha Publicación: Junio 2007
Congreso indexado en Australian Ranking of ICT Conference (CORE): categoria B
Congreso indexado en CiteSeer: 975/1221
Congreso indexado en Computer Science Conference Ranking: 0.55 (55/701)

Abstract:

This paper presents a study in which a new technique for automatically developing Artificial Neural Networks (ANNs) by means of Evolutionary Computation (EC) tools is compared with the traditional evolutionary techniques used for ANN development. The technique used here is based on network encoding on graphs and also their performance and evolution. For this comparison, 2 different real-world problems have been solved using various tools, and the results are presented here. According to them, the results obtained with this technique can beat those obtained with other ANN development tools.