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In this paper, a Box-Cox transformation-based annealing robust radial basis function networks (BCT-ARRBFNs) is proposed for training data set with skewness noise. Firstly, the initial structure is determined by a fixed BCT-ARRBFNs model which is derived by support vector regression (SVR). Secondly, the results of the SVR are used as the initial parameters of structure in the fixed BCT-ARRBFNs. At...
In this paper, the annealing robust radial basis function networks (ARRBFNs) are proposed to improve the problems of the robust radial basis function networks (RBFNs) for function approximation with outliers. Firstly, a support vector regression (SVR) approach is proposed to determine an initial structure of ARRBFNs in this paper. Because an SVR approach is equivalent to solving a linear constrained...
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