Fuzzy Logic of Non-Stationary Time Series Models with an Application

This research is dedicated to study non-stationary time series , and the ability of using fuzzy logic in order to improve forecasting. The non-stationary time series (Mixed autoregressive and moving average model) has been linked with fuzzy logic in order to get on the parameters of fuzzy time series models (Fuzzy mixed autoregressive and moving average model), and applied on monthly purchases rates data and foreign currency sales (Dollar) for the daily bid of Iraqi central bank. The fuzzy mixed autoregressive and moving average model for time series gave more appropriation forecasting than the forecasting given by fuzzy mixed autoregressive and moving average model