摘要
目前PM2.5的计算主要采用物理方法,其成本较高.为此,通过采集空气中O3,CO,PM10,SO2,NO2的浓度数据,选择神经网络方法建立PM2.5预测模型.实验结果表明,该模型对PM2.5的预测准确率较高.
At present,the calculation of PM2.5is mainly used physical methods,which is due to higher costs.Consequently,based on the concentrations of O3,CO,PM10,SO2 and NO2,the predicting model to estimate PM2.5is constructed by using neural networks.The experimental results show that a high accuracy is achieved in the model.
出处
《江苏师范大学学报（自然科学版）》
CAS
2015年第1期63-65,共3页
Journal of Jiangsu Normal University：Natural Science Edition
基金
安徽省优秀青年基金资助项目(2012SQRL227)
