Preliminary Theory of Set DR of Fuzzy Time Series Forecasting Model

Abstract

In order to solve the question which the existing fuzzy time series forecasting model prediction accuracy is not high, this paper proposes the fuzzy time series forecasting model based on differential collection of SD. The general elements expressed in SD(ï­ ). Prove: IF a time series forecasting method requires AFER<B (an arbitrary small positive number) and MSE<C (a positive number), then there exist independent variables ï­ 0(0,1), when it uses forecasting model DR for time series prediction model to simulate the problem of history data prediction research, to ensure that the average prediction error rate AFERï‚£B and mean square error MSEï‚£C was established at the same time.