Forecasting Enrollments Using Interval Length, Weightage Factor and Fuzzy Logical Relationships

Length of intervals affects forecasting results in fuzzy time series.In this paper we propose a simple method to determine the length of intervals. Based on the new obtained intervals, weightage factor and fuzzy logical relationships, higher average forecasting accuracy rate than the existing methods in the historical enrollments of the University of Alabama is obtained. The result of this method for the enrollment data are compared with other existing time series models.