Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Grammatical Evolution: Evolving Programs for an Arbitrary Language
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Exploring Grammatical Evolution for Horse Gait Optimisation
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Improving symbolic regression with interval arithmetic and linear scaling
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Grammar-based Genetic Programming: a survey
Genetic Programming and Evolvable Machines
Evolving behaviour trees for the Mario AI competition using grammatical evolution
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Genetic programming, validation sets, and parsimony pressure
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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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.