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
Link To Document :
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