基于Logistic回归算法的疫情信息查询及趋势预测系统的实现

Implementation of epidemic information query and trend prediction system based on Logistic regression algorithm

当前,新冠病毒在全球流行,各国面临严峻的疫情防控问题。文章通过统计美国每日的累计确诊病例和每日死亡人数,采用Logistic回归算法对美国疫情变化趋势进行建模,并通过大量准确数据进行预测分析。经测试,在新冠疫情暴发时,Logistic回归算法预测结果与美国累计确诊病例吻合度很高,并且疫情暴发的拐点日期也能够准确给出。通过本系统的实现,可以在疫情防控管理工作中及时掌握各地区的疫情发展变化,通过趋势预测提前做好防疫准备,及时控制疫情,提高防疫成效。

At present,the novel coronavirus is prevalent in the world,and countries are facing severe problems of epidemic prevention and control.In this paper,the daily cumulative confirmed cases and daily deaths in the United States were counted and a line chart was drawn.Logistic regression algorithm is used to model the trend of the epidemic situation in the United States,and a large amount of accurate data is used for predictive analysis.When the new crown epidemic broke out,the prediction results of the Logistic regression algorithm were very consistent with the cumulative confirmed cases in the United States,and the inflection point date of the outbreak could also be accurately given.Through the realization of this system,we can timely grasp the development and changes of the epidemic situation in various regions in the work of epidemic prevention and control management.Through trend prediction,we should prepare for epidemic prevention in advance,control the epidemic situation in time and improve the effectiveness of epidemic prevention.