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预防医学  2019, Vol. 31 Issue (1): 55-58    DOI: 10.19485/j.cnki.issn2096-5087.2019.01.013
  疾病控制 本期目录 | 过刊浏览 | 高级检索 |
应用SARIMA-GRNN组合模型分析肺结核流行的季节性特征
王华1, 田昌伟1, 王文明1, 滕国兴2
1.昆山市疾病预防控制中心,江苏 昆山 215300;
2.苏州大学公共卫生学院
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摘要 目的 应用季节性差分自回归滑动平均模型(SARIMA)和广义回归神经网络(GRNN)组合模型分析肺结核流行的季节性特征,为预防和控制肺结核提供依据。方法 通过国家卫生健康委员会官网收集2005—2017年全国肺结核疫情资料,应用SARIMA-GRNN组合模型分析我国肺结核流行的趋势和季节性特征。结果 2005—2016年我国肺结核报告发病率平均每年下降3.17%,并且发病存在明显的季节性规律(3—6月为高峰)。SARIMA (0,1,1) (0,1,1) 12 模型较好的地拟合了我国肺结核发病长期趋势和季节性,其平均误差率为6.07%,决定系数为0.73。SARIMA (0,1,1) (0,1,1) 12 -GRNN组合模型的平均误差率为2.56%,决定系数为0.94。SARIMA (0,1,1) (0,1,1) 12 - GRNN组合模型预测的准确性优于SARIMA (0,1,1) (0,1,1) 12 模型,2017年的验证数据结果与此一致。结论 2005—2016年中国肺结核报告发病率平均每年下降3.17%,肺结核的发病高峰集中在每年3—6月,具有明显的季节性。
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王华
田昌伟
王文明
滕国兴
关键词 肺结核季节性季节性差分自回归滑动平均模型广义回归神经网络    
收稿日期: 2018-07-16      出版日期: 2019-01-03
ZTFLH:  R183.3  
基金资助:昆山市社会发展科技计划项目(KS1452)
通信作者: 田昌伟,E-mail:43408197@qq.com   
作者简介: 王华,硕士,副主任医师,主要从事传染病防制管理工作
引用本文:   
王华, 田昌伟, 王文明, 滕国兴. 应用SARIMA-GRNN组合模型分析肺结核流行的季节性特征[J]. 预防医学, 2019, 31(1): 55-58.
链接本文:  
http://www.zjyfyxzz.com/CN/Y2019/V31/I1/55
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