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: 428 | Downloads: 13Download Full Article: Click HereHow to cite this article:
S Selvakumar, Kasthuri. Forecasting enrolments using fuzzy invariant Markov models. Int J Stat Appl Math 2021;6(4):104-108.
