文章摘要
朱玉,夏结来,王静.单纯ARIMA模型和ARIMA.GRNN组合模型在猩红热发病率中的预测效果比较[J].中华流行病学杂志,2009,30(9):964-968
单纯ARIMA模型和ARIMA.GRNN组合模型在猩红热发病率中的预测效果比较
Comparison of predictive effect between the single auto regressive integrated moving average(ARIMA)model and the ARIMA.generaHzed regression neural network(GRNN)combination model on the incidence of scarlet fever
投稿时间:2009-04-25  
DOI:
中文关键词: 猩红热;自回归滑动平均模型;广义回归神经网络
英文关键词: Scarlet fever;Auto regressive integrated moving average model;Generalized regression neuml network
基金项目:安徽省教育厅人文社科重点项目(2009skl92zd);安徽医科大学学术技术带头人科研资助
作者单位E-mail
朱玉 安徽医科大学公共卫生学院流行病与卫生统计学系, 合肥 230032  
夏结来 第四军医大学公共卫生学院卫生统计学教研室  
王静 安徽医科大学公共卫生学院流行病与卫生统计学系, 合肥 230032 jwan92006@126.com 
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中文摘要:
      探讨单纯求和自回归滑动平均(ARIMA)模型和求和自回归滑动平均模型与广义回归神经网络(GRNN)组合模型在猩红热发病率研究中的应用。该研究对某市2000——2006年猩红热月发病率资料建立ARIMA模型,然后将其拟合值作为GRNN的输入,实际值作为网络的输出训练网络,然后比较两个模型的效果。结果表明,单纯ARIMA模型和组合模型的平均误差率(MER)分别为31.6%、28.7%;决定系数(R2)分别为0.801、0.872。组合模型的效果要优于单纯ARIMA模型,可以用于发病率的拟合与预测。
英文摘要:
      Application of the‘single auto regressive integrated moving average(ARIMA)model’and the‘ARIMA.generalized regression neural network(GRNN) combination model’in the research of the incidence of scarlet fever.Establish the auto regressive integrated moving average model based on the data of the monthly incidence on scarlet fever of one city,from2000 to 2006.The fitting values of the ARIMA model was used as input of the GRNN。and the actualvalues were used as output of the GRNN.After仃aining the GRNN,the effect of the single ARIMAmodel and the ARlMA.GRNN combination model Was then compared.The mean error rote(MER)of the single ARIMA model and the ARIMA-GRNN combination model were 31.6%,28.7%respectively and the determination toefficient(R2)of the two models were 0.801,0.872 respectively.The fitting e伍cacy of the ARIMA.GRNN combination model was better than the single ARIMA.which had practical value in the research on time series data such as the incidence of scarlet fever.
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