摘要
随着经济的发展,空气质量问题日渐显露,雾霾天气不断增加,而雾霾形成的主要原因是细微颗粒物,细微颗粒物能够较长时间悬浮于空气中,其浓度越高危害越大。PM_(2.5)作为直径小于等于2.5微米的颗粒物,被吸入体内后会引发哮喘、支气管炎以及心血管病等疾病,引起人们的广泛关注。因此,文章对西安市2013年12月到2021年3月的PM_(2.5)浓度值共计88条数据进行了实证研究,分别采用灰色系统预测模型GM(1,1)、时间序列模型AR(2)以及二者的组合模型对西安市的PM_(2.5)进行预测,研究结果表明组合模型的相对误差最小,预测效果最优。
With the development of economy,air quality problems are increasingly exposed,and haze weather is increasing.The main reason for the formation of haze is fine particles.Fine particles can be suspended in the air for a long time,and the higher their concentration,the greater the harm.As particles with a diameter of less than or equal to 2.5 microns,PM2.5’s inhalation will lead to asthma,bronchitis,cardiovascular disease and other diseases,which has attracted extensive attention.Therefore,this paper studies a total of 88 data of PM_(2.5)concentration values from December 2013 to March 2021 in Xi’an.The grey system prediction model GM(1,1),time series model AR(2)and their combination model are used to predict the PM_(2.5)in Xi’an.The study results show that the relative error of the combined model is the smallest and the prediction effect is the best.
作者
席小雅
郑旭峰
李小鸭
XI Xiaoya;ZHENG Xufeng;LI Xiaoya(Xi’an Eurasia University,Xi’an 710065,China)
出处
《现代信息科技》
2022年第6期15-18,23,共5页
Modern Information Technology
基金
西安欧亚学院2018年度校级重点课程建设项目(2018KC022)。
