基于模糊C均值聚类分析的模糊时间序列预测中国戊型肝炎发病率
[Predicting Incidence of Hepatitis E in Chinausing Fuzzy Time Series Based on Fuzzy C-Means Clustering Analysis].
作者信息
Luo Yi, Zhang Tao, Li Xiao-song
出版信息
Sichuan Da Xue Xue Bao Yi Xue Ban. 2016 May;47(3):406-10.
OBJECTIVE
To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China.
METHODS
Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models.
RESULTS
The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model.
CONCLUSION
The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.
目的
探讨基于模糊c均值聚类的模糊时间序列模型在中国大陆戊型肝炎月发病率预测中的应用。
方法
利用2004年1月至2014年7月中国大陆戊型肝炎发病率数据建立预测模型（基于模糊c均值聚类的模糊时间序列方法）。2014年8月至2014年11月的发病率数据用于检验预测模型的拟合度。将预测结果与传统模糊时间序列模型的结果进行比较。
结果
基于模糊c均值聚类的模糊时间序列模型拟合均方误差（MSE）为0.001 1，预测MSE为6.977 5×10⁻⁴，而传统预测模型的拟合MSE和预测MSE分别为0.0017和0.0014。
结论
结果表明基于模糊c均值聚类的模糊时间序列模型在预测戊型肝炎发病率方面具有更好的性能。
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