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Interval forecasting model for time series based on the fuzzy clustering technique
Interval forecasting model for time series based on the fuzzy clustering technique
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Date
2021
Authors
T Vovan
D Phamtoan
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Research Projects
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Abstract
This paper proposes the forecasting model for the fuzzy time series based on the
improvement of the background data and fuzzy relationship (IFTC). This algorithm is built based
on the fuzzy cluster analysis which the suitable number of clusters for series is considered. The
problem of interpolating data according to fuzzy relationships of time series in the trapezoidal
fuzzy number is also established. The proposed model is illustrated step by step by a numerical
example and effectively implemented by the Matlab procedure. The IFCT has advantages in
comparing to other models via the several indexes such as the MAE, MAPE and MSE with the
Enrollment dataset.