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One-step-ahead prediction of sunspots with genetic programming

. Proceedings of the Second Nordic Workshop on Genetic Algorithms and their Applications (2NWGA), Seite 79--88. Vaasa (Finland), University of Vaasa, (19.-23.~August 1996)

Zusammenfassung

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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