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论文类型：期刊论文

发表时间：2006-01-01

发表刊物：3rd International Symposium on Neural Networks (ISNN 2006)

收录刊物：SCIE、EI、CPCI-S

卷号：3972

页面范围：741-746

ISSN号：0302-9743

摘要：In this paper, a new predictive algorithm for multivariate chaotic time series is proposed. Considering the correlations among time series, multivariate time series instead of univariate ones are taken as the inputs of predictive model. The model is implemented by a radial basis function neural network. To determine the number of model inputs, C-C method is applied to construct the embedding of the chaotic time series by choosing delay time window. The annual river runoff and annual sunspots are used in the simulation, and the proposed method is proven effective and valid.