摘要
突发公共危机事件的频繁发生已经成为社会生活中的一种常见现象。为了给政府提供决策上的参考,本文以北京市丰台区病毒性肝炎发病率的实际数据为例,利用加权马尔可夫链模型和GM(1,1)模型进行公共卫生事件传染病发病率的预测,然后比较这两种模型预测的优缺点,最后得出要根据实际的数据特点进行选择预测的结论,从而提高了预测的精度。
The frequent occurrence of sudden public crises has become a common phenomenon in the social life.In order to give the government decision-making reference,this paper predicts the incidence of infectious disease which belongs to public health events by using the weighted Markov Chain and GM（1,1） model with the actual data of the incidence of viral hepatitis in Fengtai District of Beijing,and then compares their merits and demerits.Finally,it is concluded that we should select the prediction model according to the actual characteristic of the data in order to improve the accuracy of prediction.
出处
《软件》
2012年第3期33-37,共5页
Software
基金
兰州大学交叉学科青年创新基金(LZUJC200908)
兰州大学中央高校基本科研业务(lzujbky-2012-52)
