Forecasting enrolments with high-order fuzzy time series

This paper studies the influence of a novel scheme. First-order fuzzy time series models embedded with this novel scheme become high-order. To illustrate this high-order model, the forecasting of enrolments is conducted. The results are compared with those of Chen's method and those of the Song-Chissom method. It is found that the root mean square error of the forecast can be improved from 630.86 for Chen's method and 624.23 for the Song-Chissom method to 199.32 for the proposed model.