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Time Series Forecast with Anticipation Using Genetic Programming

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Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

This paper presents and application of Genetic Programming (GP) for time series forecast. Although this kind of application has been carried out with a wide range of techniques and with very good results, this paper presents a different approach. In most of the experiments done in time series forecasting the objective is, from a consecutive set of samples or time interval, to obtain the value of the sample in the next time step. The aim of this paper is to study the forecasting not only on the next sample, but in general several samples forward. This will allow the building of more complete prediction systems. With this objective, one of the most widely used series for this kind of application has been used, the Mackey-Glass series.

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Author information

Authors and Affiliations

  1. Fac. Informatica, Univ. A Coruña, Campus Elviña, 15071, A Coruña, Spain

    Daniel Rivero, Juan R. Rabuñal, Julián Dorado & Alejandro Pazos

Authors
  1. Daniel Rivero
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  2. Juan R. Rabuñal
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  3. Julián Dorado
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  4. Alejandro Pazos
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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Rivero, D., Rabuñal, J.R., Dorado, J., Pazos, A. (2005). Time Series Forecast with Anticipation Using Genetic Programming. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_119

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  • DOI: https://doi.org/10.1007/11494669_119

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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