• DocumentCode
    1391496
  • Title

    Multi-objective genetic programming for nonlinear system identification

  • Author

    Rodríguez-Vázquez, K. ; Fleming, P.J.

  • Author_Institution
    Autom. Control & Syst. Eng., Sheffield Univ., UK
  • Volume
    34
  • Issue
    9
  • fYear
    1998
  • fDate
    4/30/1998 12:00:00 AM
  • Firstpage
    930
  • Lastpage
    931
  • Abstract
    Genetic programming is applied to the identification of non-linear polynomial models. This approach optimises multiple objectives simultaneously, and the solution set provides a trade-off between the complexity and the performance of the models. This is achieved using the concept of the non-dominated or Pareto-optimal solutions. The approach is tested on the simple Wiener model
  • Keywords
    genetic algorithms; identification; nonlinear systems; polynomials; Pareto-optimal solution; Wiener model; multi-objective genetic programming; nondominated solution; nonlinear system identification; polynomial model;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19980632
  • Filename
    682872
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1391496