Time Series Forecasting Using Fuzzy Time Series With Hedge Algebras Approach

Abstract

During the recent years, many different methods of using fuzzy time series for forecasting have been published. This paper presents a novel technique based on the hedge algebras (HA) approach. Based upon the HA, the fuzziness intervals are used to quantify the values of fuzzy time series. The intervals are determined through the fuzziness intervals and the adjusted fuzzy logical relationships. The experimental results, forecasting enrolments at the University of Alabama, demonstrate that the proposed method significantly outperforms the published ones.