A Hybrid Model to Analyze Air Pollution Spread Scales in Xian and Surrounding Cities

摘要：

　　Air quality analysis and prediction are very important in environmental research as airborne pollution has become a significant health threat, especially in Chinese urban agglomerations.Most previous analysis systems have been based on direct factors, such as pollutant concentrations, wind speeds and direction, relative humidity, and temperature;however, the air quality in a city is also affected by the air quality conditions in surrounding areas.This paper proposes a novel strategy for the analysis and forecast of air quality levels, for which Artificial Neural Networks (ANNs) are employed to elucidate the complex relationships between air quality and meteorological predictor variables.The experimental results in the study demonstrated that the normalized EEMD-ANN model outperformed other models in terms of the Precise, MAE and MAPE.The proposed model, therefore, demonstrated its potential as an administrative tool for issuing air pollution forecasts and for designing suitable abatement strategies.

关键词： air quality EEMD ANN data mining

作者: Qing Zhu Ting Wang Yiqiong Wu Jian Chai

作者单位: International Business School of Shaanxi Normal University, Xian, 710000, China;Institute of Cross- International Business School of Shaanxi Normal University, Xian, 710000, China Management and Economic School of Xidian University, Xian, 710000, China

会议类型: 国际会议

会议名称: The Seventeenth Wuhan International Conference on E-Business(第17届武汉电子商务国际会议)

会议地点: 武汉

会议语种:英文

页码: 155-164

在线出版日期: 2018-05-25（万方平台首次上网日期，不代表论文的发表时间）