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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 687313, 11 pages
Research Article

Parallel kd-Tree Based Approach for Computing the Prediction Horizon Using Wolf’s Method

1Universidad de Magallanes, Avenida Bulnes 01855, Casilla Postal 113-D, Punta Arenas, Chile
2Universidad de Castilla-La Mancha, Campus Universitario, s/n, 02071 Albacete, Spain

Received 20 July 2015; Revised 2 October 2015; Accepted 11 October 2015

Academic Editor: Meng Du

Copyright © 2015 J. J. Águila et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In different fields of science and engineering, a model of a given underlying dynamical system can be obtained by means of measurement data records called time series. This model becomes very important to understand the original system behaviour and to predict the future values of that system. From the model, parameters such as the prediction horizon can be computed to obtain the point where the prediction becomes useless. In this work, a new parallel kd-tree based approach for computing the prediction horizon is presented. The parallel approach uses the maximal Lyapunov exponent, which is computed by Wolf’s method, as an estimator of the prediction horizon.