因子-偏相关与多元回归大气污染物浓度影响关键因子识别  

Identification of Key Factors Affecting the Concentration of Air Pollutants Based on Factor Partial Correlation and Multiple Regression

作　　者：郗君甫[1] 

机构地区：[1]邢台职业技术学院信息工程系,河北邢台054035

出　　处：《电脑知识与技术》2017年第7X期190-191,195,共3页Computer Knowledge and Technology

基　　金：河北省科技计划项目(16273723)

摘　　要：为了探析引起大气污染常规污染物浓度变化主要制约因素,通过因子分析和偏相关分析的方法识别大气污染常规污染物浓度影响关键因子,并利用多元线性回归方法分析得到大气污染常规污染物浓度变化与其关键因子非标准系数多元线性回归方程,该方程式整体上能够反映出大气污染常规污染物浓度与关键因子之间的关系,为环境空气质量预报预警系统提供有效的输入因子和大气污染防控提供科学依据。In order to study the atmospheric pollution caused by changes in the concentration of conventional pollutants the major constraints, the key factors influencing the concentration of factor analysis and partial correlation analysis method for identification of atmospheric pollution and conventional pollutants, using multiple linear regression analysis method of non standard coefficient multivariate linear regression equation of atmospheric pollution conventional pollutant concentration changes and its key factor, this equation can reflect the whole the relationship between air pollution and conventional pollutant concentration of key factors, to provide scientific basis for forecasting and early warning system of environmental air quality to provide the input factor and air pollution prevention and control effectively.

关 键 词：大气污染物浓度 关键因子 因子分析 偏相关分析 

分 类 号：X51[环境科学与工程—环境工程]