Time-series prediction based on pattern classification

Abstract

In this paper, a new time-series predication method is proposed based on pattern 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 verify the effectiveness of the proposed method, several experiments are carried out on a simulation signal and real data. The results show that the proposed method has advantages over existing methods in some applications.