Temperature prediction and TAIFEX forecasting based on high-order fuzzy logical relationships and genetic simulated annealing techniques

摘要

In this paper, we present a new method for temperature prediction and the Taiwan Futures Exchange (TAIFEX) forecasting, based on high-order fuzzy logical relationships and genetic simulated annealing techniques, where simulated annealing techniques are used to deal with mutation operations of genetic algorithms. We use genetic simulated annealing techniques to adjust the length of each interval in the universe of discourse to increase the forecasting accuracy rate. The proposed method gets higher forecasting accuracy rates than the existing methods.