The L-Co-R Co-evolutionary Algorithm - A Comparative Analysis in Medium-term Time-series Forecasting Problems

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

2013

Abstract

This paper presents an experimental study in which the effectiveness of the L-Co-R method is tested. L-Co-R is a co-evolutionary algorithm to time series forecasting that evolves, on one hand, RBFNs building an appropriate architecture of net, and on the other hand, sets of time lags that represents the time series in order to perform the forecasting using, at the same time, its own forecasted values. This coevolutive approach makes possible to divide the main problem into two subproblems where every individual of one population cooperates with the individuals of the other. The goal of this work is to analyze the results obtained by {\metodo} comparing with other methods from the time series forecasting field. For that, 20 time series and 5 different methods found in the literature have been selected, and 3 distinct quality measures have been used to show the results. Finally, a statistical study confirms the good results of L-Co-R in most cases.

Paper Citation

in Harvard Style

Parras-Gutierrez E., M. Rivas V. and Merelo J. (2013). The L-Co-R Co-evolutionary Algorithm - A Comparative Analysis in Medium-term Time-series Forecasting Problems . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 144-151. DOI: 10.5220/0004555101440151

in Bibtex Style

@conference{ecta13,
author={E. Parras-Gutierrez and V. M. Rivas and J. J. Merelo},
title={The L-Co-R Co-evolutionary Algorithm - A Comparative Analysis in Medium-term Time-series Forecasting Problems},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013)},
year={2013},
pages={144-151},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004555101440151},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013)
TI - The L-Co-R Co-evolutionary Algorithm - A Comparative Analysis in Medium-term Time-series Forecasting Problems
SN - 978-989-8565-77-8
AU - Parras-Gutierrez E.
AU - M. Rivas V.
AU - Merelo J.
PY - 2013
SP - 144
EP - 151
DO - 10.5220/0004555101440151