摘要
本文主要研究基于加权马尔可夫预测模型及其在空气质量预测中的应用。首先,本文将收集到的天津市近三年来的PM2.5的日均浓度依据大气污染物浓度限值划分为6个等级;其次,运用加权马尔可夫链理论建立数学模型,并对模型进行有效性检验;最后,将利用马尔可夫链的遍历性对天津未来一段时间PM2.5浓度进行预测。结果表明:天津市未来一段时间PM2.5污染将会略微减轻,空气质量有所好转。
This paper mainly studies the Markov chain prediction model and its application in precipitation of air quality.First of all,the average daily concentration of PM2.5 collected in Tianjin in the past three years is divided into six levels according to the limits of atmospheric pollutant concentration.Then,the weighted Markov chain theory is used to establish the mathematical model,and the validity of the model is tested.Finally,the periodicity of Markov chain is used to predict the PM2.5 concentration in Tianjin in the future.The results show that the PM2.5 pollution in Tianjin will be slightly reduced and the air quality will be improved in the future.
作者
李笑盈
李可心
刘佳
梁静妮
Li Xiaoying;Li Kexin;Liu Jia;Liang Jingni(Tianjin University of Technology,Tianjin 300384,China)
出处
《科学技术创新》
2022年第23期75-78,共4页
Scientific and Technological Innovation
基金
大学生创新创业项目资助《马尔可夫链预测方法及其在天津PM2.5预测中的应用》,项目编号:201910060083。
