Abstract
In this paper, we propose a system for discovering and
optimising of various mathematical models. The system
consists of two parts. In the first part, we discover
unknown mathematical models on the basis of empirical
given data (learning data). In the second part, we
optimise parameters of the discovered mathematical
models. Genetic programming (GP) and genetic algorithm
(GA) are used for discovering and optimizing of models,
respectively. GP and GA are evolutionary optimization
methods based on the Darwinian natural selection and
survival of the fittest.
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