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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Chaos Synthesis by Evolutionary Algorithms
verfasst von : Ivan Zelinka, Guanrong Chen, Sergej Celikovsky
Erschienen in: Evolutionary Algorithms and Chaotic Systems
Verlag: Springer Berlin Heidelberg
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This chapter introduces the notion of chaos synthesis by means of evolutionary algorithms and develops a new method for chaotic systems synthesis. This method is similar to genetic programming and grammatical evolution and is applied alongside evolutionary algorithms: differential evolution, self-organizing migrating, genetic algorithm, simulated annealing and evolutionary strategies. The aim of this investigation is to synthesize new and “simple” chaotic systems based on some elements contained in a pre-chosen existing chaotic system and a properly defined cost function. The investigation consists of two case studies based on the aforementioned evolutionary algorithms in various versions. For all algorithms, 100 simulations of chaos synthesis were repeated and then averaged to guarantee the reliability and robustness of the proposed method. The most significant results are carefully selected, visualized and commented in this chapter.