Step 3: Fuzzify historical dataIn this context, fuzzification is the process of identifying associations between the historical values in the dataset and the fuzzy sets defined in the previous step. Each historical value is fuzzified according to its highest degree of membership. If the highest degree of belongingness of a certain historical time variable, say F t−1 , occurs at fuzzy set Ak, then F t−1 is fuzzified as Ak. To exemplify this, let us fuzzify year 1971. According to table 4, the enrollment in 1971 was 13055 which lies within the boundaries of interval u1. Since the highest membership degree of u1 occurs at A1, the historical time variable F 1971 is fuzzified as A1. Actual enrollment of 1974 is 14696 which lies within the boundaries of interval u2. Hence F 1974 is fuzzified as A2. A complete overview of fuzzified enrollments is shown in the table 5.
đang được dịch, vui lòng đợi..
