Comment on 'Parameters identification of chaotic systems by quantum-behaved particle swarm optimization' [Int. J. Comput. Math. 86(12) (2009), pp. 2225-2235]

S. Jafari, S. M.R.H. Golpayegani, Ayoub Daliri

Research output: Contribution to journalComment/debate

9 Citations (Scopus)

Abstract

This note comments on a published article 'Parameters identification of chaotic systems by quantum-behaved particle swarm optimization'. In this article, similarity between time series obtained from chaotic systems is considered as a measure of similarity between them; however, it is well known that this method is not suitable for chaotic systems.

Original languageEnglish (US)
Pages (from-to)903-905
Number of pages3
JournalInternational Journal of Computer Mathematics
Volume90
Issue number5
DOIs
StatePublished - May 1 2013
Externally publishedYes

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Chaotic systems
Parameter Identification
Chaotic System
Particle swarm optimization (PSO)
Particle Swarm Optimization
Identification (control systems)
Time series
Similarity

Keywords

  • chaotic systems
  • chaotic time series
  • Henon map
  • parameters identification
  • sensitivity to initial conditions

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

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abstract = "This note comments on a published article 'Parameters identification of chaotic systems by quantum-behaved particle swarm optimization'. In this article, similarity between time series obtained from chaotic systems is considered as a measure of similarity between them; however, it is well known that this method is not suitable for chaotic systems.",
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AU - Jafari, S.

AU - Golpayegani, S. M.R.H.

AU - Daliri, Ayoub

PY - 2013/5/1

Y1 - 2013/5/1

N2 - This note comments on a published article 'Parameters identification of chaotic systems by quantum-behaved particle swarm optimization'. In this article, similarity between time series obtained from chaotic systems is considered as a measure of similarity between them; however, it is well known that this method is not suitable for chaotic systems.

AB - This note comments on a published article 'Parameters identification of chaotic systems by quantum-behaved particle swarm optimization'. In this article, similarity between time series obtained from chaotic systems is considered as a measure of similarity between them; however, it is well known that this method is not suitable for chaotic systems.

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KW - chaotic time series

KW - Henon map

KW - parameters identification

KW - sensitivity to initial conditions

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