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A novel nonlinear time series prediction method based on the dynamic clustering neural network is proposed. This method selects prediction samples which are similar with training samples according to the cluster analysis based on the dynamic characteristics of samples and then a new subset of the samples is obtained. All of the samples in this subset have the similar dynamic characteristics. By training...
The coupled relationship and mutual interaction between the global sea surface temperature (SST) and the global sea level (GSL) is one of key questions about global change. However, non-uniform distribution, nonlinearity and complex mechanism make so many uncertainties on the multiscale relationship between them. In this paper, BEMD and DTW methods are combined to investigate the multiscale interactions...
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