RT Conference Proceedings
T1 Automatic design of artificial neural networks to forecast time series
A1 Peralta, Juan
A1 Gutiérrez Sánchez, Germán
A1 Sanchis de Miguel, María Araceli
AB In 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 shown
PB Ibergarceta
SN 978-84-92812-62-2
YR 2010
FD 2010
LK https://hdl.handle.net/10016/12504
UL https://hdl.handle.net/10016/12504
LA eng
NO Actas de: III Simposio de Inteligencia Computacional, SICO 2010, Valencia, 8-10 septiembre, 2010
DS e-Archivo
RD 3 jun. 2024