摘要
针对模糊时间序列模型中模糊推理规则的优化问题,提出一种时间序列的自相关理论与模糊时间序列相结合的算法.首先考查数据平稳化;然后运用传统的数据模糊化方法得到模糊集,进而建立模糊规则,并运用自相关函数理论对模糊规则进行优化;最后通过对Alabama大学注册人数的预测验证了所提出算法的有效性.
Facing with the optimization problem of fuzzy rules in the fuzzy time series forecasting model, an algorithm is proposed to optimize fuzzy rules by combing auto-correlation theory with fuzzy time series. Firstly, data stationarity is discussed and then fuzzy sets are obtained by using the traditional data fuzzification method, thereby fuzzy rules are established. Fuzzy rules are optimized by using the auto-correlation theory. Finally, through the forecasting of Alabama university enrollments, results show the effectiveness of the proposed method.
出处
《控制与决策》
EI
CSCD
北大核心
2015年第10期1797-1802,共6页
Control and Decision
基金
国家自然科学基金项目(60875032/F030504)
中央高校基本科研业务费专项基金项目(2012TD032)
关键词
模糊时间序列
自相关函数
规则权重
特征展开法
fuzzy time series
autocorrelation function
rules weights
characteristic expansion method
