From the beginning, forecasting of time series events like weather forecasting, accidents prediction, enrolments forecasting, stock prices etc has drawn attention of many people. A lot of work has been done in the forecasting field where data is in linguistic form. In current paper, an innovative method is proposed to forecast the time series of higher order which is fuzzy in nature to enhance the estimateprecision and the speed of forecasting. The method is applied on the benchmark problem of student’s enrolment. Comparison of results obtained is done on the basis of error analysis and this approach is found to be better than some of the pre-existing methods.
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