A Fuzzy Time Series Forecasting Model Based on Yearly Difference of the Student Enrollment Number

Abstract

A number of forecasting models have been proposed based on fuzzy time series in the past 20 years, and forecasting accuracy rate continues to increase. This paper establishes a fuzzy time series forecasting model based on yearly difference of the student enrollment number. The method uses the yearly difference of the student enrollment number as domain to establish a fuzzy number, inverse fuzzy number and prediction formula. The forecasting process is illustrated by applying history student enrollment number of the University of Alabama, and forecasting accuracy rate is higher than that of the existing method.