Automated Input Variable Selection for Analog Methods Using Genetic Algorithms
Pascal Horton,
Olivia Martius,
Simon Lukas Grimm
Abstract:Analog methods (AMs) have long been used for precipitation prediction
and climate studies. However, they rely on manual selections of
parameters, such as predictor variables and analogy criteria. Previous
work showed the potential of genetic algorithms (GAs) to optimize most
of the AM parameters. This research goes one step further and
investigates the potential of GAs for automating the selection of the
input variables and the analogy criteria (distance metric between two
data fields) in AMs. Our study focuse… Show more
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