摘要
为了研究广州市空气质量变化趋势问题,提出了一种通过引入季节因子构建灰色SGM(1,1)模型,再用Markov模型修正的方法,经检验可知,修正SGM(1,1)模型的平均相对误差仅为3.17%,均方差比值和小误差概率均达到一级精度;利用改进模型对广州市未来四年空气污染物浓度进行预测,结果显示:1) N02和03的浓度逐年缓慢增长,其他污染物则逐年缓慢下降;2)除PM10和SO2之外的其他污染物浓度均未达到二级标准值,需要有关部门持续监测和治理.
In order to study the changing trend of air quality in Guangzhou,a method of constructing gray SGM(1,1) model by introducing seasonal factors and modifying it with Markov model is proposed.The test shows that the average relative error of the modified SGM(1,1)model is only 3.17%,and the mean square error ratio and small error probability are all of the first order accuracy.Using the improved model to forecast the air pollutant concentration in Guangzhou in the next four years,the results show that:1) the concentration of NO2 and O3 increases slowly year by year,while other pollutants decrease slowly year by year;2) the concentration of other pollutants except PM10 and SO2 does not reach the secondary standard value,which requires continuous monitoring and control by relevant departments.
作者
崔庆岳
赵国瑞
朱志鑫
CUI Qing-yue;ZHAO Guo-rui;ZHU Zhi-xin(Mathematical Model Laboratory Guangzhou City Construction College,Guangzhou 510925,China;Department of Basic Courses Teaching Ordos Vocational College,Ordos 017000,China)
出处
《数学的实践与认识》
北大核心
2020年第1期201-208,共8页
Mathematics in Practice and Theory
基金
广东省重点科研平台和科研项目(2018GKQNCK128).
