Peralta, JuanGutiérrez Sánchez, GermánSanchis de Miguel, María Araceli2011-11-042011-11-042010Rojas Ruiz, Ignacio; Pomares Cintas, Héctor; Herrera Maldonado, Luis Javier (eds.). Actas del III Simposio de Inteligencia Computacional, SICO 2010 : Jornadas organizadas por Capítulo Español de la IEEE Computational Intelligence Society. Madrid: Ibergarceta, 2010, p. 237-342. ISBN 978-84-92812-62-2978-84-92812-62-2https://hdl.handle.net/10016/12504Actas de: III Simposio de Inteligencia Computacional, SICO 2010, Valencia, 8-10 septiembre, 2010In this work an approach to design Artificial Neural Networks (ANN) to forecast Time Series is tackled. The approach is an automatic method that is carried out by an Evolutionary Algorithm (as a search algorithm) to design ANN. A key issue for these kinds of approaches is what information is included into the chromosome that represents an ANN There are two principal ideas about this question: first, the chromosome contains information about parameters of the topology, architecture, learning parameters, etc. of the ANN. The results using a parameter Encoding Scheme to design ANN for a Time Series Competition are shownapplication/pdfengAtribución-NoComercial-SinDerivadas 3.0 EspañaArtificial Neural NetworksTime SeriesEvolutionary computationForecastingEvolutionary algorithmsconference paperInformáticaopen access237342Actas del III Simposio de Inteligencia Computacional, SICO 2010 : Jornadas organizadas por Capítulo Español de la IEEE Computational Intelligence Society