An Air Quality Predictive Model of Licang of Qingdao City Based on BP Neural Network

摘要：

　　In order to obtain high precision reults of urban air quality forecast,we propose a short-term predictive model of air quality in this paper,which is on the basis of the ambient air quality monitoring data and relevant meteorological data of a monitoring site in Lieang district of Qingdao city in recent three years.The predietive model is based on BP neural network and used to predict the ambient air quality in the next some day or within a certain period of hours.In the design of the predietive model,we apply LM algorithm,Simulated Annealing algorithm and Early Stopping algorithm into BP network,and use a reasonable method to extract the historical data of two years as the training smples,which are the main reasons why the prediction results are better both in speed and in accuracy.And when predieting within a certain period of hours,we also adopt an average and equivalent idea to reduce the error accuracy,which brings us good results.

关键词： prediction air quality BP neural network

作者: Ruobo Xin Zhifang Jiang Ning Li Lujian Hou

作者单位: School of Computer Science & Technology Shandong University Jinan, 250101, China Jinan Academy of Environmental sciences Jinan, 250014, China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer and Information Applications(ICCIA2012)(2012第二届计算机和信息应用国际会议)

会议地点: 太原

会议语种:英文

页码: 415-418

在线出版日期: 2012-12-08（万方平台首次上网日期，不代表论文的发表时间）