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Evolving Interpolating Models of Net Ecosystem CO2 Exchange Using Grammatical Evolution

  • Miguel Nicolau
  • Matthew Saunders
  • Michael O’Neill
  • Bruce Osborne
  • Anthony Brabazon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7244)

Abstract

Accurate measurements of Net Ecosystem Exchange of CO 2 between atmosphere and biosphere are required in order to estimate annual carbon budgets. These are typically obtained with Eddy Covariance techniques. Unfortunately, these techniques are often both noisy and incomplete, due to data loss through equipment failure and routine maintenance, and require gap-filling techniques in order to provide accurate annual budgets. In this study, a grammar-based version of Genetic Programming is employed to generate interpolating models for flux data. The evolved models are robust, and their symbolic nature provides further understanding of the environmental variables involved.

Keywords

Grammatical evolution Real-world applications Symbolic regression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Miguel Nicolau
    • 1
  • Matthew Saunders
    • 2
  • Michael O’Neill
    • 1
  • Bruce Osborne
    • 2
  • Anthony Brabazon
    • 1
  1. 1.Natural Computing Research & Applications GroupUniversity College DublinDublinIreland
  2. 2.UCD School of Biology and Evironmental ScienceUniversity College DublinDublinIreland

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