A Novel High Order Fuzzy Time Series Forecasting Method with Higher Accuracy Rate

Fuzzy time series have been extensively used to make predictions of weather, road accidents, academic enrollments, population, and stock prices. In this paper, we have introduced an improved fuzzy time series forecasting model. This new model is applied in forecasting the University of Alabama student enrollments. Later a comparison has been done with some of the existing fuzzy time series forecasting methods being carried out on the same data set for university student enrollments. It has been observed that the proposed model has improved forecasting accuracy as well as reduced model complexity compared to other methods.