Abstract
In this paper we describe the application of an architecture for an ensemble neural network for Complex Time Series Prediction. The times series we are considering are: the Mackey-Glass, Dow Jones and Mexican Stock Exchange and we show the results of a set of trainings with the ensemble neural network, and its integration with the methods of average, weighted average and Fuzzy Integration. Simulation results show very good prediction of the ensemble neural network with fuzzy logic integration.
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Pulido, M., Mancilla, A., Melin, P. (2009). An Ensemble Neural Network Architecture with Fuzzy Response Integration for Complex Time Series Prediction. In: Castillo, O., Pedrycz, W., Kacprzyk, J. (eds) Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control. Studies in Computational Intelligence, vol 257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04514-1_6
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DOI: https://doi.org/10.1007/978-3-642-04514-1_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04513-4
Online ISBN: 978-3-642-04514-1
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