基于多元线性回归的PM2.5浓度预测

J. Chen, Jianbo Wang
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引用次数: 9

摘要

随着雾霾天气的频繁发生,雾霾天气的主要污染物PM2.5的浓度预测逐渐成为热门话题。本文在分析长沙市PM2.5历史数据和相关气象信息的基础上,建立了预测PM2.5浓度的多元线性回归模型。通过与观测值的比较,验证了模型的有效性。该模型对PM2.5浓度预测具有较好的应用价值。
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Prediction of PM2.5 Concentration Based on Multiple Linear Regression
With the frequent occurrence of haze weather, the concentration prediction of PM2.5, the main pollutant in haze weather, has gradually become a hot topic. Based on the analysis of historical data of PM2.5 and related weather information in Changsha City, this paper establishes a multivariate linear regression model to predict the concentration of PM2.5. The validity of the model is verified by comparing the predicted value with the observed value. The model has a good application value for the prediction of PM2.5 concentration.
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