我国病毒性肝炎感染和死亡人数预测分析
Prediction of Viral Hepatitis Infection and Death in China
摘要: 病毒性肝炎是一种危害肝脏的极具传染性的疾病,可有多种肝炎相关病毒诱发。在我国每年感染病毒性肝炎的人数都在1百万以上,且病毒性肝炎的传染性较强,对于我国这样一个世界人口大国而言,对病毒性肝炎的预防工作尤为重要。于是本研究以2011~2019年我国病毒性肝炎感染人数和死亡人数为基础,分别采用传统的GM(1,1)预测模型、BP神经网络预测模型和一元线性回归预测模型对2020~2029年病毒性肝炎感染人数和死亡人数进行预测,并在考虑到模型本身产生的系统性误差的基础上,利用各模型预测平均完全误差二次方根占比为权重将3种预测模型的预测结果进行加权平均作为最终的预测结果。最终得出结论病毒性肝炎感染人数在未来10年呈现显著的下降趋势,但病毒性肝炎死亡人数却呈现上涨趋势。
Abstract:
Viral hepatitis is a very infectious disease that endangers the liver and can be induced by a variety of hepatitis related viruses. The number that infects virus hepatitis in our country every year is in 1 million above, and the infectivity of virus hepatitis is stronger, to our country such a world’s most populous country, the preventive work to virus hepatitis is particularly important. Therefore, based on the number of viral hepatitis infections and deaths in China from 2011 to 2019, this study used the traditional GM(1,1) prediction model, BP neural network prediction model and univariate linear regression prediction model respectively to predict the number of viral hepatitis infections and deaths from 2020 to 2029. On the basis of considering the systematic error of the model itself, the quadratic root ratio of the average complete error of each model is used as the weight and the weighted average of the prediction results of the three models is taken as the final prediction result. It is concluded that the number of viral hepatitis infection will decrease significantly in the next 10 years, but the number of viral hepatitis deaths will increase.
参考文献
|
[1]
|
吴小清, 许阳婷, 苏晶晶, 徐庆, 王炜翔. 1989~2020年南京市病毒性肝炎流行趋势分析[J]. 预防医学, 2021, 33(3): 236-240+245.
|
|
[2]
|
邓炯. 2005~2018年绵阳市涪城区病毒性肝炎流行特征统计分析[J]. 预防医学情报杂志, 2020, 36(8): 1049-1054.
|
|
[3]
|
陈晓娥, 查成喜, 赵子莹. 2010~2020年某三甲医院患者病毒性肝炎实验室结果特征分析[J]. 甘肃科技, 2021, 37(8): 80-82+62.
|
|
[4]
|
李金伟, 王瑞瑞. 基于灰色模型的信阳市老龄化人口趋势预测[J]. 现代商贸工业, 2021, 42(8): 46-47.
|
|
[5]
|
徐丽丽, 李洪, 李劲. 基于灰色预测和径向基网络的人口预测研究[J]. 计算机科学, 2019, 46(S1): 431-435.
|
|
[6]
|
李自鹏, 欧向军, 周蓓蓓, 钱嘉琳, 欧亚根. 徐州市人口发展特征及其预测[J]. 江苏师范大学学报(自然科学版), 2021, 39(1): 21-25.
|
|
[7]
|
钟恒恺. 基于数学模型的南京旅游人数预测与方案优化[J]. 通讯世界, 2018, 25(12): 262-264.
|