Method for predicting atmospheric PM2.5 concentration based on VARX model

The invention provides a method for predicting atmospheric PM2.5 concentration based on a VARX model. The method comprises the following steps of: (1), collecting pollutant concentration data and meteorological data of a target city; (2), reading the pollutant data and the meteorological data of the target city from a database; (3), performing principal component analysis of the data, except PM2.5; (4), performing a root test of a data set; (5), constructing a VARX equation model; (6), determining a lagged order of the model by using an AIC Akaike information criterion and a SC Schwarz criterion; and (7), predicting the PM2.5 concentration by correcting and using the VARX model. The method disclosed by the invention has the characteristics of being relatively high in generalization ability, relatively high in prediction precision and the like. 本发明提供了种基于VARX模型的大气PM浓度预测方法，其包括如下步骤：步骤、收集目标城市的污染物浓度数据及气象数据；步骤二、从数据库中读出目标城市的污染数据和气象数据；步骤三、对除PM以外的数据进行主成分分析；步骤四、对数据集进行根检验；步骤五、构造VARX方程模型；步骤六、使用AIC赤池信息量准则和SC施瓦兹准则来确定模型的滞后阶数