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.
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References
Moffat, A., et al.: Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes. Agricultural and Forest Meteorology 147, 209–232 (2007)
Azad, R.M.A., Ansari, A.R., Ryan, C., Walsh, M., McGloughlin, T.: An evolutionary approach to wall shear stress prediction in a grafted artery. Applied Soft Computing 4(2), 139–148 (2004)
Brabazon, A., O’Neill, M.: Biologically Inspired Algorithms for Financial Modelling. Springer, Heidelberg (2006)
Falge, E., et al.: Gap filling strategies for defensible annual sums of net ecosystem exchange. Agricultural and Forest Meteorology 107, 43–69 (2001)
Gagné, C., Schoenauer, M., Parizeau, M., Tomassini, M.: Genetic Programming, Validation Sets, and Parsimony Pressure. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds.) EuroGP 2006. LNCS, vol. 3905, pp. 109–120. Springer, Heidelberg (2006)
Goulden, M., Munger, W., Fan, S.M., Daube, B., Wofsy, S.: Measurements of carbon sequestration by long-term eddy covariance: methods and critical evaluation of accuracy. Global Change Biology 2, 169–182 (1996)
Harper, R.: GE, explosive grammars and the lasting legacy of bad initialisation. In: Proceedings of IEEE Congress on Evolutionary Computation, CEC 2010, July 18-23, Barcelona, Spain, pp. 2602–2609. IEEE Press (2010)
Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press (1975)
Hui, D., Wan, S., Su, B., Katul, G., Monson, R., Luo, Y.: Gap-filling missing data in eddy covariance measurements using multiple imputation (mi) for annual estimates. Agricultural and Forest Meteorology 121, 93–111 (2004)
Humphreys, E., Black, T.A., Morgenstern, K., Cai, T., Drewitt, G., Nesic, Z., Trofymow, J.: Carbon dioxide fluxes in coastal douglas-fir stands at different stages of development after clearcut harvesting. Agricultural and Forest Meteorology 140, 6–22 (2006)
Keijzer, M.: Improving Symbolic Regression with Interval Arithmetic and Linear Scaling. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 70–82. Springer, Heidelberg (2003)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press (1992)
Reichstein, M., et al.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11, 1424–1439 (2005)
McKay, R.I., Nguyen, X.H., Whigham, P.A., Shan, Y., O’Neill, M.: Grammar-based genetic programming - a survey. Genetic Programming and Evolvable Machines 11(3-4), 365–396 (2010)
Murphy, J.E., O’Neill, M., Carr, H.: Exploring Grammatical Evolution for Horse Gait Optimisation. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds.) EuroGP 2009. LNCS, vol. 5481, pp. 183–194. Springer, Heidelberg (2009)
Nicolau, M.: Automatic grammar complexity reduction in grammatical evolution. In: Poli, R., et al. (eds.) Genetic and Evolutionary Computation Conference (GECCO) Workshops. AAAI (2004)
O’Neill, M., Ryan, C.: Grammatical Evolution - Evolutionary Automatic Programming in an Arbitrary Language. Genetic Programming, vol. 4. Kluwer Academic (2003)
Papale, D., Valentini, R.: A new assessment of european forests carbon exchanges by eddy fluxes and artificial neural network spatialization. Global Change Biology 9, 525–535 (2003)
Perez, D., Nicolau, M., O’Neill, M., Brabazon, A., Yannakakis, G.N.: Evolving Behaviour Trees for the Mario AI Competition Using Grammatical Evolution. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcázar, A.I., Merelo, J.J., Neri, F., Pruess, M., Richter, H., Togelius, J., Yannakakis, G.N. (eds.) EvoApplications 2011, Part I. LNCS, vol. 6624, pp. 123–132. Springer, Heidelberg (2011)
Pingintha, N., Leclerc, M., Beasley, J., Durden, D., Zhang, G., Senthong, C., Rowland, D.: Hysteresis response of daytime net ecosystem exchange during drought. Biogeosciences 7, 1159–1170 (2010)
Ryan, C., Azad, A.: Sensible initialisation in grammatical evolution. In: Cantú-Paz, E., et al. (eds.) Genetic and Evolutionary Computation Conference (GECCO) Workshops. AAAI (2003)
Ryan, C., Collins, J., O’Neill, M.: Grammatical Evolution: Evolving Programs for an Arbitrary Language. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391, pp. 83–95. Springer, Heidelberg (1998)
Tuite, C., Agapitos, A., O’Neill, M., Brabazon, A.: A Preliminary Investigation of Overfitting in Evolutionary Driven Model Induction: Implications for Financial Modelling. In: Di Chio, C., Brabazon, A., Di Caro, G.A., Drechsler, R., Farooq, M., Grahl, J., Greenfield, G., Prins, C., Romero, J., Squillero, G., Tarantino, E., Tettamanzi, A.G.B., Urquhart, N., Uyar, A.Ş. (eds.) EvoApplications 2011, Part II. LNCS, vol. 6625, pp. 120–130. Springer, Heidelberg (2011)
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Nicolau, M., Saunders, M., O’Neill, M., Osborne, B., Brabazon, A. (2012). Evolving Interpolating Models of Net Ecosystem CO2 Exchange Using Grammatical Evolution. In: Moraglio, A., Silva, S., Krawiec, K., Machado, P., Cotta, C. (eds) Genetic Programming. EuroGP 2012. Lecture Notes in Computer Science, vol 7244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29139-5_12
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DOI: https://doi.org/10.1007/978-3-642-29139-5_12
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