Abstract
Grammatical Evolution (GE) is a grammar-based form of Genetic Programming. One important operator in GE algorithms is the selection scheme. The objective of this study is a comparison of two models of survivor selection, the generalation replacement and steady state, for use in tidal level forecasting. The survivor selection schemes are compared and evaluated according to their properties. The results show the performence of steady state is 95,66 % and 94,39 % for generalation replacement.
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