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

作者:

Highlights:

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.

论文关键词:Two-factors high-order fuzzy time series,Two-factors high-order fuzzy logical relationships,Max–min composition,Genetic algorithms

论文评审过程:Available online 8 June 2006.

论文官网地址:https://doi.org/10.1016/j.eswa.2006.05.015