A simple method of forecasting based on fuzzy time series

In fuzzy time series forecasting various methods have been developed to establish the fuzzy relations on time series data having linguistic values for forecasting the future values. However, the major problem in fuzzy time series forecasting is the accuracy in the forecasted values. The present paper proposes a new method of fuzzy time series forecasting based on difference parameters. The proposed method is a simplified computational approach for the forecasting. The method has been implemented on the historical enrollment data of University of Alabama (adapted by Song and Chissom) and the forecasted values have been compared with the results of the existing methods to show is superiority. Further, the proposed method has also been implemented on a real life problem of crop production forecast of wheat crop and the results have been compared with other methods.