Forecasting using fuzzy time series invariant model

Forecasting shows a dynamic part in numerous fields such as, rainfall forecasting, stock market forecasting, weather forecasting and so on. In recent years, fuzzy time series is used for forecasting the time series data. Song and Chissom (1993) proposed fuzzy time series for forecasting the enrollments of University of Alabama. Shiva Raj Singh(2007) presented a simple time variant method for forecasting the enrollments of University of Alabama. In the present work, a modified fuzzy time series algorithm is used for such type of problems. The forecasting results are better than the existing methods.  Mean Square Error (MSE) is mininimum when comparing the existing methods. The results were displayed numerically and graphically.