偏最小二乘回归分析在空气质量监测数据校准中的应用

Application of Partial Least Squares Regression Analysis in the Calibration of Air Quality Monitoring Data

为了对空气质量监测数据进行合理校准,在对产生误差因素分析的基础上,运用偏最小二乘回归分析理论,建立监测数据校准的数学模型.利用2019年全国大学生数学建模竞赛D题所提供的数据,对模型进行仿真检验.结果表明,偏最小二乘回归分析模型可以有效地对空气质量监测数据进行校准,提高监测数据的精度.

In order to properly calibrate the air quality monitoring data,On the basis of the analysis of the er⁃ror factors,a mathematical model for monitoring data calibration is established by the theory of partial least squares regression.Using the data from 2019 national university students′mathematical contest in modeling D problem,the model was tested by simulation.The results show that the partial least squares regression mod⁃el can effectively calibrate the air quality data and improve the accuracy of the monitoring data.