Department of Physics, Nankai University, Tianjin 300071, China
Abstract:
The least squares support vector machine (LS-SVM) is
used to study the nonlinear time series prediction. First, the
parameter γ and multi-step prediction capabilities of the
LS-SVM network are discussed. Then we employ clustering method
in the model to prune the number of the support values. The
learning rate and the capabilities of filtering noise for LS-SVM
are all greatly improved.