Time-series prediction based on pattern classification

In this paper, a new time-series predication method is proposed based on pa ttern analysis. In this method, basic patterns and their probabilities are extracted from a time series. A probabilistic relaxation method is employed to classify the probability vectors of the basic patterns. In order to ver ify the effectiveness of the proposed method, several experiments are carri ed out on a simulation signal and real data. The results show that the prop osed method has advantages over existing methods in some applications. (C) 2001 Elsevier Science Ltd. All rights reserved.