A Comparison Between ANN Generation and Training Methods and Their Development by Means of Graph Evolution: 2 Sample Problems

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.

• Type: Conference
• Year: 2007
• Where: IWANN
• Authors: Daniel Rivero, Julian Dorado, Juan R. Rabuñal, Marcos Gestal
• Keywords: ANN Development, Artificial Neural Networks, IWANN 2007, Traditional Evolutionary Techniques