• DocumentCode
    305391
  • Title

    A genetic algorithm solution to the maximum likelihood statistical problem

  • Author

    Varricchio, Sergio ; Cheim, Luiz

  • Author_Institution
    Center for Electr. Energy Res., CEPEL, Rio de Janeiro, Brazil
  • Volume
    3
  • fYear
    1996
  • fDate
    14-17 Oct 1996
  • Firstpage
    1983
  • Abstract
    The paper describes an application of a genetic algorithm (GA) computer software called Gen S, developed at CEPEL, with the support of major Brazilian utilities, in the solution of a complex statistical problem involving the maximization of the so called likelihood function. The problem, as described below, is associated with the complete statistical characterization of a given dielectric insulation, such as an air gap, from just a few observations of the gap behavior under certain stress conditions (high voltage signal applied to the gap a limited number of times). Besides comparing the results with a modified Newton-Raphson method, the authors point out the ease of use of Gen S as well as its major advantages regarding analytical and more conventional numerical methods
  • Keywords
    genetic algorithms; insulating materials; maximum likelihood estimation; physics computing; software packages; statistical analysis; Gen S; air gap; complete statistical characterization; dielectric insulation; gap behavior; genetic algorithm solution; likelihood function; maximum likelihood statistical problem; modified Newton-Raphson method; Air gaps; Application software; Dielectrics and electrical insulation; Equations; Genetic algorithms; Probability distribution; Stress; Test facilities; Testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1996., IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-3280-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.1996.565431
  • Filename
    565431