Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 33, Issue 3, Pages 539-550Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2006.05.015
Keywords
two-factors high-order fuzzy time series; two-factors high-order fuzzy logical relationships; max-min composition; genetic algorithms
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In this paper, we present a new method for temperature prediction and the TAIFEX forecasting based on fuzzy logical relationships and genetic algorithms. The proposed method constructs two-factors high-order fuzzy logical relationships based on the historical data and uses genetic algorithms to adjust the length of each interval in the universe of discourse for temperature prediction and the TAIFEX forecasting to increase the forecasting accuracy rate. The proposed method gets a higher forecasting accuracy rate than the existing methods. (c) 2006 Elsevier Ltd. All rights reserved.
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