UM  > 科技學院  > 電腦及資訊科學系
Effect of choice of kernel in support vector machines on ambient air pollution forecasting
Yang J.Y.; Ip W.F.; Vong C.M.; Wong P.K.
2011-08-24
Conference Name2011 International Conference on System Science and Engineering
Source PublicationProceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
Pages552-557
Conference Date8-10 June 2011
Conference PlaceMacao, China
Abstract

Forecasting of air pollution is a popular and important topic in recent year 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 practicians and 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 (SVM), 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. © 2011 IEEE.

KeywordPollution Level Forecasting Support Vector Machines Svm Kernel
DOI10.1109/ICSSE.2011.5961964
URLView the original
Language英语
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Yang J.Y.,Ip W.F.,Vong C.M.,et al. Effect of choice of kernel in support vector machines on ambient air pollution forecasting[C],2011:552-557.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang J.Y.]'s Articles
[Ip W.F.]'s Articles
[Vong C.M.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang J.Y.]'s Articles
[Ip W.F.]'s Articles
[Vong C.M.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang J.Y.]'s Articles
[Ip W.F.]'s Articles
[Vong C.M.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.