• DocumentCode
    3783799
  • Title

    A multi-objective evolutionary algorithm for fuzzy modeling

  • Author

    F. Jimenez;A.F. Gomez-Skarmeta;H. Roubos;R. Babuska

  • Author_Institution
    Control Eng. Lab., Delft Univ. of Technol., Netherlands
  • Volume
    2
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    1222
  • Abstract
    In this paper a multi-objective evolutionary algorithm with a single run is proposed in order to consider several objectives dealing with transparency and compactness in obtaining a fuzzy model besides the standard accuracy objective. In this way the use of Pareto-optimal solutions within the evolutionary algorithm let us obtain attractive fuzzy models with respect to compactness, transparency and also accuracy. The results of the combination of Pareto-based multi-objective evolutionary algorithms and fuzzy modeling are compared with other approaches in the literature.
  • Keywords
    "Evolutionary computation","Fuzzy sets","Fuzzy neural networks","Neural networks","Pareto optimization","Control engineering","Laboratories","Fuzzy control","Takagi-Sugeno model","Unsupervised learning"
  • Publisher
    ieee
  • Conference_Titel
    IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
  • Print_ISBN
    0-7803-7078-3
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2001.944781
  • Filename
    944781