Prediction of hourly PM2.5 using a space-time support vector regression model | |
Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang | |
刊名 | Atmospheric Environment |
2018 | |
卷号 | Vol.181页码:12-19 |
关键词 | Real-time air quality prediction Spatial heterogeneity Spatial dependence Support vector regression Spatial clustering Gauss vector weight function |
ISSN号 | 1352-2310 |
URL标识 | 查看原文 |
公开日期 | [db:dc_date_available] |
内容类型 | 期刊论文 |
URI标识 | http://www.corc.org.cn/handle/1471x/5468410 |
专题 | 湖南大学 |
作者单位 | 1.National-local Joint Engineering Laboratory of Geospatial Information Technology, Hunan University of Science and Technology, Xiangtan, China 2.Department ofGeo-Informatics, Central South University, Changsha, China 3.China Railway First Survey |
推荐引用方式 GB/T 7714 | Yang, Wentao,Deng, Min,Xu, Feng,et al. Prediction of hourly PM2.5 using a space-time support vector regression model[J]. Atmospheric Environment,2018,Vol.181:12-19. |
APA | Yang, Wentao,Deng, Min,Xu, Feng,&Wang, Hang.(2018).Prediction of hourly PM2.5 using a space-time support vector regression model.Atmospheric Environment,Vol.181,12-19. |
MLA | Yang, Wentao,et al."Prediction of hourly PM2.5 using a space-time support vector regression model".Atmospheric Environment Vol.181(2018):12-19. |
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