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2016 | OriginalPaper | Chapter

A Radial Basis Function Neural Network-Based Coevolutionary Algorithm for Short-Term to Long-Term Time Series Forecasting

Authors : E. Parras-Gutierrez, V. M. Rivas, J. J. Merelo

Published in: Computational Intelligence

Publisher: Springer International Publishing

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Abstract

This work analyzes the behavior and effectiveness of the L-Co-R method using a growing horizon to predict. This algorithm performs a double goal, on the one hand, it builds the architecture of the net with a set of RBFNs, and on the other hand, it sets a group of time lags in order to forecast future values of a time series given. For that, it has been used a set of 20 time series, 6 different methods found in the literature, 4 distinct forecast horizons, and 3 distinct quality measures have been utilized for checking the results. In addition, a statistical study has been done to confirms the good results of the method L-Co-R.

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Title: A Radial Basis Function Neural Network-Based Coevolutionary Algorithm for Short-Term to Long-Term Time Series Forecasting
Authors: E. Parras-Gutierrez
V. M. Rivas
J. J. Merelo
Publisher: Springer International Publishing
Book: Computational Intelligence
Print ISBN: 978-3-319-23391-8

Electronic ISBN: 978-3-319-23392-5

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-319-23392-5_7

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