Identification Method for Evolution of Time Series with Poor Information Using Grey System Theory

Abstract

Based on the grey system theory, a new method is presented to identify evolution of time series with poor information. Via definition of the original state sequence and the evolution state sequence, the information element function along with the grey confidence level is introduced into the criterion for identification of the stability of time series. The simulation test of initial worn stages of a mechanical device shows that without any prior information of trends and functions, the method can effectively recognize and evaluate the state of evolution of time series. It follows that corresponding measures in a timely manner can be taken and serious accidents can be avoided.