| Status | 已發表Published |
| Air Quality Modelling using Support Vector Machines | |
Vong, C. M. ; Ip, W.F.; Wong, P. K.; Yang, Y.Y.
| |
| 2012-03-01 | |
| Source Publication | Journal of Control Science and Engineering (EI)
 |
| ISSN | 1687-5257 |
| Pages | 1-11 |
| Abstract | Forecasting of air pollution is a popular and important topic in recent years due to the health impact caused by air pollution. It is necessary to build an early warning system, which provides forecast and also alerts health alarm to local inhabitants by medical practitioners and the local government. Meteorological and pollutions data collected daily at monitoring stations of Macau can be used in this study to build a forecasting system. Support vector machines (SVMs), a novel type of machine learning technique based on statistical learning theory, can be used for regression and time series prediction. SVM is capable of good generalization while the performance of the SVM model is often hinged on the appropriate choice of the kernel. |
| Keyword | Air pollution Support Vector Machines |
| Language | 英語English |
| The Source to Article | PB_Publication |
| PUB ID | 8003 |
| Document Type | Journal article |
| Collection | Faculty of Science and Technology |
| Corresponding Author | Vong, C. M. |
| Recommended Citation GB/T 7714 | Vong, C. M.,Ip, W.F.,Wong, P. K.,et al. Air Quality Modelling using Support Vector Machines[J]. Journal of Control Science and Engineering (EI), 2012, 1-11. |
| APA | Vong, C. M.., Ip, W.F.., Wong, P. K.., & Yang, Y.Y. (2012). Air Quality Modelling using Support Vector Machines. Journal of Control Science and Engineering (EI), 1-11. |
| MLA | Vong, C. M.,et al."Air Quality Modelling using Support Vector Machines".Journal of Control Science and Engineering (EI) (2012):1-11. |
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