Evolving Interpolating Models of Net Ecosystem CO2 Exchange Using Grammatical Evolution

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Title: Evolving Interpolating Models of Net Ecosystem CO2 Exchange Using Grammatical Evolution
Authors: Nicolau, Miguel
Saunders, Matthew
O'Neill, Michael
Osborne, Bruce A.
Brabazon, Anthony
Permanent link: http://hdl.handle.net/10197/8177
Date: 13-Apr-2012
Abstract: Accurate measurements of Net Ecosystem Exchange of CO2 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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2012 Springer
Keywords: Grammatical evolutionReal-world applicationsSymbolic regression
DOI: 10.1007/978-3-642-29139-5_12
Language: en
Status of Item: Peer reviewed
Is part of: Moraglio, A., Silva, S., Krawiec, K., Machado, P. and Cotta, C. Proceedings: Genetic Programming: 15th European Conference (EuroGP 2012) (Lecture Notes in Computer Science Volume 7244)
Conference Details: Genetic Programming: 15th European Conference (EuroGP 2012) Malaga, Spain, 11-13 April 2012
Appears in Collections:Business Research Collection
Biology & Environmental Science Research Collection

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