Preprocessing in Fuzzy Time Series to Improve the Forecasting Accuracy

Abstract

The preprocessing in fuzzy time series has an important role to improve the forecast accuracy. The definitions of domain, number of linguistic terms and of the membership function to each fuzzy set, has direct influence in the forecast results. Thus, this paper has the focus on definition of these parameters, before of performing the prediction. The experimental results in enrollments time series show that, when the forecast is performed after proposed preprocessing, the accuracy rate is improved.