International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2021, Vol. 6, Issue 4, Part B

Forecasting enrolments using fuzzy invariant Markov models


Author(s): S Selvakumar and Kasthuri

Abstract: The forecast predicts the future events of time series. Forecasting plays a key role in various fields such as weather forecasting, economic and business planning, etc. Song and Chissom (1994) proposed fuzzy time series and pioneered this model. In this work, an efficient fuzzy time series forecasting model based on fuzzy clustering to handle forecasting problems and improving forecasting accuracy. Each value (observation) is represented by a fuzzy set. The fuzzy sets are converted into the Transition Probability Matrix (TPM). The invariant Markov models are compared with existing models. The results are displayed numerically and graphically.

Pages: 104-108 | Views: 46 | Downloads: 7

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How to cite this article:
S Selvakumar, Kasthuri. Forecasting enrolments using fuzzy invariant Markov models. Int J Stat Appl Math 2021;6(4):104-108.
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