Forecasting TAIEX using improved type 2 fuzzy time series

This paper presents a new method to forecast TAIEX based on a high-order type 2 fuzzy time series. Extra observations are used to improve forecasting performance. Extra observations are modeled as type 2 fuzzy sets and fourth-order fuzzy time series. Our proposed model outperforms previous studies.

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