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灰色模型在某部队肺结核预测中的应用
引用本文:卢娟,杨春梅,宫占威,王辉. 灰色模型在某部队肺结核预测中的应用[J]. 疾病监测, 2012, 27(7): 573-575. DOI: 10.3784/j.issn.1003-9961.2012.7.021
作者姓名:卢娟  杨春梅  宫占威  王辉
作者单位:兰州军区疾病预防控制中心疾病监控科,甘肃兰州,730020
基金项目:兰州军区后勤科研计划(No.CLZ11J05)~~
摘    要:目的 探索某部队肺结核发病规律,利用预测模型对其发病率进行预测,为部队相关部门制定针对性的防控措施提供参考依据。 方法 根据某部队2001-2010年的肺结核发病率,应用灰色预测系统,建立肺结核的发病率预测模型,并进行中长期的预测。 结果 预测模型为:X(1)(k+1)=-179.369 574e-0.049 677k+190.669 574。检验表明,该模型精度为2级,能较好地对肺结核发病进行中长期预测。预测结果显示,2011-2013年该部队肺结核发病率分别为5.559/万、5.290/万、5.033/万。 结论 模型适用于某部队肺结核发病率预测,并且肺结核发病率以每年4.82%的幅度缓慢下降。

关 键 词:灰色模型   肺结核   预测
收稿时间:2012-01-07

Application of grey model in predicting pulmonary tuberculosis incidence in a military unit
LU Juan , YANG Chun-mei , GONG Zhan-wei , WANG Hui. Application of grey model in predicting pulmonary tuberculosis incidence in a military unit[J]. Disease Surveillance, 2012, 27(7): 573-575. DOI: 10.3784/j.issn.1003-9961.2012.7.021
Authors:LU Juan    YANG Chun-mei    GONG Zhan-wei    WANG Hui
Affiliation:.Center for Disease Control and Prevention of Lanzhou Military Command,Lanzhou 730020,Gansu,China
Abstract:Objective To explore the incidence pattern of pulmonary tuberculosis(TB) and predict its incidence by grey model in a military unit,and provide the theoretical evidence for health department in the development of prevention and control measure.Methods According to the incidence data of pulmonary TB in the military unit from 2001 to 2010,a predicting model of pulmonary TB incidence was built to carried out moderate and long term predicting research.Results The predicting model was(1)(k+1)=-179.369 574e-0.049 677k+190.669 574,and the estimation test result of model was qualified and the model was capable in predicting moderate and long term pulmonary TB incidence.The predicting result indicated that the pulmonary TB incidence in the military unit would be 5.559/104,5.290/104,5.033/104 from 2011 to 2013.Conclusion The model is suitable for the prediction of pulmonary TB incidence in the military unit,which indicates that the annual incidence of pulmonary TB will decrease by 4.82% from 2011 to 2013.
Keywords:grey model  tuberculosis  prediction
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