DocumentCode :
1175696
Title :
Adaptive CAD-Model Construction Schemes
Author :
Lamecki, Adam ; Balewski, Lukasz ; Mrozowski, Michal
Author_Institution :
Gdansk Univ. of Technol., Gdansk
Volume :
45
Issue :
3
fYear :
2009
fDate :
3/1/2009 12:00:00 AM
Firstpage :
1538
Lastpage :
1541
Abstract :
Two advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF) interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied with respect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, the performance of the ANN models obtained with a new training scheme is superior and comparable to the rational function models.
Keywords :
CAD; electronic engineering computing; interpolation; neural nets; radial basis function networks; sampling methods; adaptive CAD; adaptive sampling; artificial neural networks; histograms; radial basis function interpolation; surrogate model construction; Artificial neural networks (ANNs); CAD models; multivariate rational interpolation; radial basis functions (RBF);
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2009.2012736
Filename :
4787284
Link To Document :
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