Elsevier

Fuzzy Sets and Systems

Volume 54, Issue 1, 25 February 1993, Pages 1-9
Fuzzy Sets and Systems

Forecasting enrollments with fuzzy time series — Part I

https://doi.org/10.1016/0165-0114(93)90355-LGet rights and content

Abstract

There have been a good many methods to forecast university enrollments in the literature. However, none of them could be applied when the historical data are linguistic values. Fuzzy time series is an effective tool to deal with such problems. In this paper, as an application of fuzzy time series in educational research, the forecast of the enrollments of the University of Alabama is carried out. In so doing, a fuzzy time series model is developed using historical data. A complete procedure is proposed which includes: fuzzifying the historical data, developing a fuzzy time series model, and calculating and interpreting the outputs. To evaluate the forecasting model, the robustness of the fuzzy time series model is tested. Advantages and problems of the forecasting method are also discussed.

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