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Temperature prediction and TAIFEX forecasting based on fuzzy logical relationships and genetic algorithms

机译:基于模糊逻辑关系和遗传算法的温度预测和TAIFEX预测

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摘要

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.
机译:在本文中,我们提出了一种基于模糊逻辑关系和遗传算法的温度预测和TAIFEX预测的新方法。该方法基于历史数据构造了两因素高阶模糊逻辑关系,并使用遗传算法调整了话语空间中每个区间的长度,以进行温度预测和TAIFEX预测,从而提高了预测的准确率。与现有方法相比,该方法具有较高的预测准确率。

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