A new forecasting method of discrete dynamic system

摘要

Usually, a linear differential equation is used to represent continuous dynamic systems, but a linear difference equation is used to represent discrete dynamic systems. AGO is one of the most important characteristics of grey theory, and its main purpose is to reduce the random of data. A linear differential equation, instead of a linear difference equation, is used to replace the grey differential equation to analyze discrete systems in this paper. The k-order derivatives of 1-AGO data are calculated after cubic spline interpolation of them, and the model parameters are estimated by means of the deterministic convergence scheme. ARIMA models are used to analyze the leading indicator in advance, and Fourier series with suitably chosen values of parameters is used for fitting the leading indicator. The model presented in this paper is called Grey Dynamic Model GDM(1,1,1).