An approach to handel nondeterminism in fuzzy time series forecasting by hesitant fuzzy sets

In this present study, we have addressed the issue of hesitancy in fuzzy set based forecasting method that occurs due to the availability of several fuzzification method of time series data and propose integrated fuzzy time series forecasting method with hesitant fuzzy sets. In this study, partition the universe of discourse and used triangular and Gaussian fuzzy membership function to construct hesitant fuzzy sets. Further to this hesitant fuzzy element are aggregated by a suitable aggregation operator to construct fuzzy logical relations. Proposed forecasting method is implemented over the historical enrollments of Alabama University. The outperformance is tested over other forecasted models under the error measure, validation test and statistical analysis.