By Krebs A., Stephan E.P.
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Extra info for A p-version finite element method for nonlinear elliptic variational inequalities in 2D
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Although, the FNNs trained using the PCA projection of the data set, in general, provide high classiﬁcation accuracy, there is no straightforward way to select the right number of factors for each problem. K. Tasoulis et al. 5%, for the optimal selection of the number of factors. The above discussion suggests that the UkW algorithm is capable of automatically identifying meaningful groups of features, while the PCA technique optimally transforms the data set, with limited loss of information, to a space of signiﬁcantly lower dimension.
A p-version finite element method for nonlinear elliptic variational inequalities in 2D by Krebs A., Stephan E.P.