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- W2399730599 abstract "Model construction is usually guided by a trial-error process, where each iteration is divided into two steps: (i) physical modeling and (ii) identification. Genetic programming has been applied to automate this process in different ways. One of the most complete approaches is the described in project SMOG, where a set of model structures is evolved, being the set of parameters of each model optimized by means of classical methods. In this paper, a GA-P algorithm (a hybrid between genetic algorithms and genetic programming) is applied to the task permitting the evolution in parallel of model structures and parameters." @default.
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- W2399730599 date "2002-01-01" @default.
- W2399730599 modified "2023-09-25" @default.
- W2399730599 title "GA-P BASED MODELING OF NONLINEAR DYNAMIC SYSTEMS" @default.
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- W2399730599 doi "https://doi.org/10.3182/20020721-6-es-1901.01012" @default.
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