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This paper proposes a novel fuzzy forecasting method for forecasting the TAIEX based on optimal partitions of intervals, optimal weights, and particle swarm optimization (PSO) techniques. First, it applies PSO techniques to find optimal intervals and optimal weighting vectors of two-factors second-order fuzzy-trend logical relationship groups (TFSTLRGs) simultaneously using the historical training...
This paper presents a new method for fuzzy forecasting based on two-factors high-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. We fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors high-order fuzzy logical relationships. Then, we group the two-factors high-order fuzzy logical relationships...
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