Fuzzy Time Series Forecasting of Low Dimensional Numerical Data
نویسندگان
چکیده
Various classical techniques such as linear regression, nearest neighbor have been used in developing predictive models in the past. But the methodologies developed using fuzzy time series includes a wide array of work that requires special attention. The time series analysis has been of great importance to engineering and economy problems. In this paper, we present a brief summary of the various infamous methodologies available in the literature for forecasting of numerical data using fuzzy time series that includes stock prediction, temperature prediction, foreign exchange daily price estimate, crop production, educational enrollments forecasting, inventory demand and also a brief mention of the limitations of fuzzy time series.
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