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  • This paper deals with the optimization of control of Hénon Map, which is a discrete chaotic system. This paper introduces and compares evolutionary approach representing tuning of parameters for an existing control method, as well as meta-evolutionary approach representing synthesis of whole control law by means of Analytic Programming (AP). These two approaches are used for the purpose of stabilization of the stable state and higher periodic orbits, which stand for oscillations between several values of chaotic system. For experimentation, Self-Organizing Migrating Algorithm (SOMA) and Differential Evolution (DE) were used.
  • This paper deals with the optimization of control of Hénon Map, which is a discrete chaotic system. This paper introduces and compares evolutionary approach representing tuning of parameters for an existing control method, as well as meta-evolutionary approach representing synthesis of whole control law by means of Analytic Programming (AP). These two approaches are used for the purpose of stabilization of the stable state and higher periodic orbits, which stand for oscillations between several values of chaotic system. For experimentation, Self-Organizing Migrating Algorithm (SOMA) and Differential Evolution (DE) were used. (en)
Title
  • Evolutionary and Meta-Evolutionary Approach for the Optimization of Chaos Control
  • Evolutionary and Meta-Evolutionary Approach for the Optimization of Chaos Control (en)
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  • Evolutionary and Meta-Evolutionary Approach for the Optimization of Chaos Control
  • Evolutionary and Meta-Evolutionary Approach for the Optimization of Chaos Control (en)
skos:notation
  • RIV/70883521:28140/12:43868976!RIV13-MSM-28140___
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  • P(ED2.1.00/03.0089), S
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  • 135315
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  • RIV/70883521:28140/12:43868976
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  • Chaos control, Evolutionary algorithms, Optimization, Symbolic regression, SOMA, Differential evolution (en)
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  • [BC5461394494]
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  • Zakopane
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  • Heidelberg
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  • Swarm and Evolutionary Computation
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  • Oplatková, Zuzana
  • Zelinka, Ivan
  • Šenkeřík, Roman
  • Davendra, Donald
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issn
  • 0302-9743
number of pages
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  • 10.1007/978-3-642-29353-5_41
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  • Springer-Verlag. Berlin
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  • 978-3-642-29352-8
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  • 28140
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