DocumentCode :
1219424
Title :
Electrode-spacer contour optimization by ANN aided genetic algorithm
Author :
Lahiri, A. ; Chakravorti, S.
Author_Institution :
Dept. of Electr. Eng., Jadavpur Univ., India
Volume :
11
Issue :
6
fYear :
2004
Firstpage :
964
Lastpage :
975
Abstract :
Optimization of contours of three dimensional electrode-spacer arrangements used in gas insulated systems (GIS) has been carried out by ANN aided genetic algorithm (GA) to obtain desirable electric stress distribution along the insulator surface. Two cases have been studied and reported in detail. Multilayer feed-forward neural networks with error back-propagation algorithm have been applied to accelerate the execution of GA loop. The training and the test data have been prepared by means of electric field calculations using indirect boundary element method (BEM). The results show that optimized contours have been obtained with acceptable degree of accuracy with the help of GA aided by trained ANN.
Keywords :
backpropagation; boundary-elements methods; electric fields; electrodes; feedforward neural nets; gas insulated substations; gas insulated switchgear; genetic algorithms; ANN; BEM; GA; GIS; artificial neural network; boundary element method; electric field; electric stress; electrode-spacer; error back-propagation algorithm; gas insulated systems; genetic algorithm; multilayer feed-forward neural networks; optimization; Artificial neural networks; Dielectrics and electrical insulation; Feedforward neural networks; Feedforward systems; Gas insulation; Genetic algorithms; Geographic Information Systems; Multi-layer neural network; Neural networks; Stress;
fLanguage :
English
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
Publisher :
ieee
ISSN :
1070-9878
Type :
jour
DOI :
10.1109/TDEI.2004.1387819
Filename :
1387819
Link To Document :
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