Abstract
Timeinvariant nonlinear one-step-ahead prediction
models were developed by genetic programming. As a test
case benchmark sunspot series was used. Functional form
and numerical parameters of the models were optimized.
The generalisation ability, i.e. final suitability, of
the predictors was assessed through crossvalidation.
The results were compared to those of threshold
autoregression and neural network -based predictors of
the sunspot benchmarks found in literature. Standard
GP-approach is shown not to be sufficient to solve this
prediction problem as well as the methods in comparison
do.
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