Biological Cybernetics
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
An extended evaluation framework for neural network publications in sales forecasting
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Shuffle design to improve time series forecasting accuracy
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural Networks is carried out by a Genetic Algorithm. A key issue for these kinds of approaches is what information is included in the chromosome that represents an Artificial Neural Network. In this approach new information will be included into the chromosome so it will be possible to compare these results with those obtained in a previous approach. There are two principal ideas to take into account: first, the chromosome contains information about parameters of the topology, architecture, learning parameters, etc. of the Artificial Neural Network, i.e. Direct Encoding Scheme; second, the chromosome contains the necessary information so that a constructive method gives rise to an Artificial Neural Network topology (or architecture), i.e. Indirect Encoding Scheme. The results for a Direct Encoding Scheme (in order to compare with Indirect Encoding Schemes developed in future works) to design Artificial Neural Networks to forecast Time Series are shown.