Evolutionary Algorithms and Chaotic Systems

Volume 267 of the series Studies in Computational Intelligence pp 265-291

Evolutionary Reconstruction of Chaotic Systems

  • Ivan ZelinkaAffiliated withFaculty of Applied Informatics, Tomas Bata University in ZlinFaculty of Electrical Engineering and Computer Science, VSB-TUO
  • , Ales RaidlAffiliated withFaculty of Mathematics and Physics, Charles University

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This chapter discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Five different evolutionary algorithms are presented and tested in a total of 13 and 12 versions in two different versions of experiments. System selected for numerical experiments here is the well-known logistic equation. For each algorithm and its version, 100 repeated simulations were conducted. According to obtained results it can be stated that evolutionary reconstruction is an alternative and a promising way as to how to identify chaotic systems.