A Novel Fuzzy Time Series Forecasting Method Based on Fuzzy Logical Relationships and Similarity Measures

This paper proposes a new fuzzy forecasting method for forecasting the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time series, fuzzy logical relationships, the K-means clustering algorithm, and similarity measures. The proposed fuzzy forecasting method gets higher forecasting accuracy rates than the existing methods.

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