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Displaying similar documents to “Evolutionary prototype selection.”

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Angelova, Maria, Tzonkov, Stoyan, Pencheva, Tania (2010)

Serdica Journal of Computing

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Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for...

Self-adaptation of parameters in a learning classifier system ensemble machine

Maciej Troć, Olgierd Unold (2010)

International Journal of Applied Mathematics and Computer Science

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Self-adaptation is a key feature of evolutionary algorithms (EAs). Although EAs have been used successfully to solve a wide variety of problems, the performance of this technique depends heavily on the selection of the EA parameters. Moreover, the process of setting such parameters is considered a time-consuming task. Several research works have tried to deal with this problem; however, the construction of algorithms letting the parameters adapt themselves to the problem is a critical...