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- Title
Una modificación de la metodología de regresión simbólica para la predicción de series de tiempo.
- Authors
Martínez, Carlos A.; Velásquez-Henao, Juan D.
- Abstract
In this paper we propose a new methodology for the prediction of nonlinear time series using genetic programming. The proposed approach is based on incorporating the concept of functional blocks and the modification of the genetic algorithm so that it operates with it. The functional blocks represent well known statistical models for the time series forecasting. The proposed algorithm allows the exploration and exploitation of regions where there is greater possibility of finding better forecasting models. Two Benchmark time series were predicted in order to validate the proposed approach, and it was found that our methodology predicts more accurately the time series considered, in comparison with other nonlinear models.
- Subjects
REGRESSION analysis; MATHEMATICAL models of forecasting; TIME series analysis; NONLINEAR statistical models; GENETIC algorithms; GENETIC programming; ARTIFICIAL neural networks
- Publication
Ingeniería y Universidad, 2013, Vol 17, Issue 2, p325
- ISSN
0123-2126
- Publication type
Article