[自回归积分滑动平均模型在湖南省食物中毒预测中的应用]
[Autoregressive integrated moving average model in food poisoning prediction in Hunan Province].
作者信息
Chen Ling, Xu Huilan
机构信息
School of Public Health, Central South University, Changsha, China.
出版信息
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2012 Feb;37(2):142-6. doi: 10.3969/j.issn.1672-7347.2012.02.005.
OBJECTIVE
To determine the application of autoregressive integrated moving average (ARIMA) model in food poisoning prediction in Hunan Province, and to provide scientific basis for the prevention and control of food poisoning.
METHODS
We collected the number of food poisoning from January 2003 to December 2009 in Hunan Province for ARIMA model fitting, and used food poisoning data of 2010 to verify the effect of model prediction. We predicted the number of food poisoning in 2011.
RESULTS
ARIMA (0,1,1) (0,1,1)12 better fit the trends of the poisoning number in previous time periods and series, with prediction fitting error of 9.59%. The number of food poisoning in Hunan Province in 2011 was predicted to be 834.
CONCLUSION
ARIMA model can better fit the number of food poisoning in the short term trends and series. If used for long-term forecasts.
目的
探讨自回归积分滑动平均（ARIMA）模型在湖南省食物中毒预测中的应用，为食物中毒的预防控制提供科学依据。
方法
收集湖南省2003年1月至2009年12月食物中毒发生起数进行ARIMA模型拟合，并采用2010年食物中毒数据验证模型预测效果，对2011年食物中毒发生起数进行预测。
结果
ARIMA（0,1,1）（0,1,1）12能较好地拟合前期食物中毒起数的变化趋势及序列，预测拟合误差为9.59%，预测2011年湖南省食物中毒发生起数为834起。
结论
ARIMA模型能够较好地拟合食物中毒起数的短期变化趋势及序列，可用于短期预测。
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