The Set of Ternary Time Series Forecasting Models Based on the Ordered Difference of Difference

Abstract

This paper proposed a set of ternary time series forecasting models based on the ordered difference of difference method. When predicting the registered number at the University of Alabama in 1971~1992 years, the computer can find forecasting model as Fx(0.00004,0.9,0.00004) using automatic optimization search method, which can make the mean square error MSE=0 and the average forecasting error rate AFER=0%. For any time series, this forecasting accuracy can be obtained, which improved comprehensively the forecasting accuracy of the existing fuzzy time series forecasting model.