摘要
PM2.5作为大气首要污染物,严重影响着人们的健康。为了研究PM2.5的成因、分布、扩散规律,文中提出"多元线性回归模型",通过研究PM2.5与其他大气指标间的相关程度来分析PM2.5的成因;使用"小波分析"分析西安地区的13个监测点PM2.5浓度值的变化,并描述其PM2.5的时空分布规律;使用"高斯模型"直观地看出在扩散点源影响下的安全和严重污染区域,在保证计算精度的前提下提高了计算效率。每个模型都通过仿真结果证明了其有效性和实用性。
As the primary air contaminants, PM2.5 has a serious impact on human health. In order to study on the causes, distribution and diffusion rule of PM2. 5, this paper proposes ＂ multiple linear regression model ＂, by studying on the degree of correlation between PM2.5 and other atmospheric indicators to analyze the causes of PM2. 5 ;analyzing the changes of concentration values of 13 monitoring sites in Xi＇an by using wavelet analysis and describing the distribution of PM2. 5 in time and space. The safety and serious pollution area can be intuitively seen under the influence of diffusion point by using the Gaussian model, under the premise of ensuring the accuracy, the model improved the computational efficiency, every model demonstrated the effectiveness and practicality by the simulation results.
出处
《信息技术》
2014年第11期1-6,11,共6页
Information Technology
基金
国家自然科学基金项目(61170277)
上海市教委科研创新重点项目(12zz137)
上海市一流学科建设项目(S1201YLXK)
关键词
多元线性回归模型
小波分析
高斯模型
multiple linear regression model
wavelet analysis
Gaussian model
