DocumentCode :
3012524
Title :
Comparison of some neural network algorithms used in prediction of XLPE HV insulation properties under thermal aging
Author :
Boukezzi, Larbi ; Boubakeur, A.
Author_Institution :
Mater. Sci. & Inf. Labortory, Djelfa Univ., Djelfa, Algeria
fYear :
2012
fDate :
23-27 Sept. 2012
Firstpage :
1218
Lastpage :
1222
Abstract :
Some Artificial neural network algorithms have been used to predict properties of high voltage electrical insulation under thermal aging in term to reduce the aging experiment time. In this paper we present a short comparison of the obtained results in the case of Cross-linked Polyethylene (XLPE). The theoretical and the experimental results are concordant. As a neural network application, we propose a new method based on Radial Basis Function Gaussian network (RBFG) trained by two algorithms: Random Optimization Method (ROM) and Back-propagation (BP).
Keywords :
XLPE insulation; ageing; backpropagation; optimisation; power engineering computing; radial basis function networks; XLPE HV insulation properties prediction; artificial neural network algorithms; back-propagation; concordant; cross-linked polyethylene; high voltage electrical insulation; neural network application; radial basis gaussian network; random optimization method; thermal aging; Aging; Artificial neural networks; Insulation; Prediction algorithms; Read only memory; Training; Neural network; Prediction; XLPE insulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Condition Monitoring and Diagnosis (CMD), 2012 International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4673-1019-2
Type :
conf
DOI :
10.1109/CMD.2012.6416381
Filename :
6416381
Link To Document :
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