Automatic design of artificial neural networks to forecast time series

Abstract

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