Novel real time predictor for complex time series

The task of complex time series predicting is hard to be accomplished with only one single predicting model. In this paper, a novel multi-scale incremental predictor is proposed. This predictor decomposes the complex time series into a series of intrinsic mode functions (IMF) and a residual signal with empirical mode decomposition firstly, and then an Incremental Independent Vector Combination Predicting algorithm in Kernel Space (IIVCPKS) is constructed for predicting every IMF or residual signal. The proposed predictor is competent for predicting the complex time series in real time. Experimental results showed that the proposed method performed very well in the task of predicting complex time series.