RBNNRadial Basis Neural Network
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The figure suggests that the HGA has more ability to adapt to discontinuities and sharp peaks in curves despite the level of noise and the small number of samples in contrast to GRNN and RBNN methods.
In most cases in Figures 4 and 5, the upper quartile of the MSE values for the HGA is under the first quartile of those from the RBNN or GRNN methods.
The columns correspond from left to right to the GRNN, HGA, and RBNN methods, respectively (solid line estimated function; dashed line real function).