Fuzzy random auto-regression time series model in enrollment university forecasting

Abstract

The statistical models required the large data in the time series forecasting. While, to forecast the limited data or small data cannot be suggested by using these models. In this paper, we are interested to apply fuzzy random auto-regression model to handle the university enrollment data. The accuracy of the forecasting model can be improved through the left-right procedure. The yearly enrollment data of Alabama University are examined as benchmark data to evaluate the performance of proposed model. The results indicate that the smaller left-right spread of triangular fuzzy number produced the higher forecasting accuracy if compared with the existing models.