Forecasting model of intuitionistic fuzzy time series using ratio distribution

Nguyen Thi Thu Dung, L.V. Chernenkaya


Time series forecasting modeling is an area of intensive research and development. Nowadays, the application of fuzzy logic to time series forecasting models has attracted much attention and developed widely. At this time, the intuitionistic fuzzy time series model is not only a new approach, but also demonstrates high forecasting performance when nondeterminism is taken into account. In this paper, a modified intuitionistic fuzzy time series forecasting model is proposed based on discretization optimization based on the determination of the optimal ratio using the allocation algorithm. The model is applied to a real time series forecasting problem obtained from historical data at the University of Alabama from 1971 to 1992. The mean square errors (MSE) of the obtained forecasting results are presented. The superiority of the proposed model is demonstrated by comparing it with existing models.

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