A forecasting approach of fuzzy time series model based on a new data fuzzification

Abstract

In view of the research about fuzzy time series models, the existing models are lack of objective data fuzzification and sensitivity. In this paper, firstly, a new method of defining fuzzy sets present is set up and six new fuzzy sets are given. Secondly, the rules of data fuzzification are defined. Finally, the model is used to forecast the enrollments of the University of Alabama. It is shown that the proposed model gets a higher forecasting accuracy than those which use traditional methods to forecast.