15. Evolving Rules for Local Time Series Prediction

  1. Enrique Alba1,
  2. Christian Blum2,
  3. Pedro Isasi3,
  4. Coromoto León4 and
  5. Juan Antonio Gómez5
  1. C. Luque,
  2. J. M. Valls and
  3. P. Isasi

Published Online: 16 MAY 2008

DOI: 10.1002/9780470411353.ch15

Optimization Techniques for Solving Complex Problems

Optimization Techniques for Solving Complex Problems

How to Cite

Luque, C., Valls, J. M. and Isasi, P. (2009) Evolving Rules for Local Time Series Prediction, in Optimization Techniques for Solving Complex Problems (eds E. Alba, C. Blum, P. Isasi, C. León and J. A. Gómez), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470411353.ch15

Editor Information

  1. 1

    Universidad de Málaga, Dpto. de Lenguajes y Ciencias de la Computación, Málaga, Spain

  2. 2

    Universitat Politècnica de Catalunya, Dpto. de Llenguatges i Sistemes Informàtics, Barcelona, Spain

  3. 3

    Universidad Carlos III de Madrid, Dpto. de Informática, Escuela Politécnica Superior, Madrid, Spain

  4. 4

    Universidad de La Laguna, Dpto. de Estadística, I.O. y Computación, La Laguna, Spain

  5. 5

    Universidad de Extremadura, Dpto. de Tecnologías de Computadores y Comunicaciones, Escuela Politécnica, Cáceres, Spain

Author Information

  1. Universidad Carlos III de Madrid, Dpto. de Informática, Escuela Politécnica Superior, Madrid, Spain

Publication History

  1. Published Online: 16 MAY 2008
  2. Published Print: 6 FEB 2009

Book Series:

  1. Wiley Series on Parallel and Distributed Computing

Book Series Editors:

  1. Albert Y. Zomaya

ISBN Information

Print ISBN: 9780470293324

Online ISBN: 9780470411353

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Keywords:

  • Venice lagoon;
  • autoregressive moving average (ARMA);
  • Michigan approach

Summary

This chapter contains sections titled:

  • Introduction

  • Evolutionary Algorithms for Generating Prediction Rules

  • Experimental Methodology

  • Experiments

  • Conclusions

  • References