Genetic programming-based chaotic time series modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Wei Zhang and Zhi-ming Wu and Gen-ke Yang",
  title =        "Genetic programming-based chaotic time series
  journal =      "Journal of Zhejiang University Science",
  year =         "2004",
  volume =       "5",
  number =       "11",
  pages =        "1432--1439",
  keywords =     "genetic algorithms, genetic programming, PSO, Chaotic
                 time series analysis, Genetic programming modelling,
                 Nonlinear Parameter Estimation (NPE), Particle Swarm
                 Optimization, Nonlinear system identification",
  ISSN =         "1009-3095",
  URL =          "",
  DOI =          "doi:10.1631/jzus.2004.1432",
  size =         "8 pages",
  abstract =     "This paper proposes a Genetic Programming-Based
                 Modeling (GPM) algorithm on chaotic time series. GP is
                 used here to search for appropriate model structures in
                 function space, and the Particle Swarm Optimization
                 (PSO) algorithm is used for Nonlinear Parameter
                 Estimation (NPE) of dynamic model structures. In
                 addition, GPM integrates the results of Nonlinear Time
                 Series Analysis (NTSA) to adjust the parameters and
                 takes them as the criteria of established models.
                 Experiments showed the effectiveness of such
                 improvements on chaotic time series modeling.",
  notes =        "Department of Automation, Shanghai Jiaotong
                 University, Shanghai 200030, China

                 JZUS Document code: A CLC
                 number: TN914

                 chaotic Chebyshev-map",

Genetic Programming entries for Wei Zhang Zhi-Ming Wu Gen-Ke Yang