Interval forecasting with Fuzzy Time Series

In recent years, the demand for developing low computational cost methods to deal with uncertainty in forecasting has been increased. Interval forecasting is a category of forecasting in which the method provides intervals as outputs of its forecasting. The initial aim of this paper is therefore proposing a new interval forecasting method based on a low cost and accurate forecasting method, namely first order Fuzzy Time Series. In this study, the results of the proposed method are compared with actual data and regular point forecasts using Fuzzy Time Series. The evaluation of the results shows the accuracy and promising performance of the proposed method.