Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines

Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines

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 governmen...

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Main Authors: Chi-Man Vong, Weng-Fai Ip, Pak-kin Wong, Jing-yi Yang
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Journal of Control Science and Engineering
Online Access:http://dx.doi.org/10.1155/2012/518032
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spelling doaj-7b623a1fc28340c6bb08d697ca49ff802020-11-24T21:45:15ZengHindawi LimitedJournal of Control Science and Engineering1687-52491687-52572012-01-01201210.1155/2012/518032518032Short-Term Prediction of Air Pollution in Macau Using Support Vector MachinesChi-Man Vong0Weng-Fai Ip1Pak-kin Wong2Jing-yi Yang3Department of Computer and Information Science, University of Macau, MacauFaculty of Science and Technology, University of Macau, MacauDepartment of Electromechanical Engineering, University of Macau, MacauDepartment of Computer and Information Science, University of Macau, MacauForecasting 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.http://dx.doi.org/10.1155/2012/518032
collection DOAJ
language English
format Article
sources DOAJ
author Chi-Man Vong
Weng-Fai Ip
Pak-kin Wong
Jing-yi Yang
spellingShingle Chi-Man Vong
Weng-Fai Ip
Pak-kin Wong
Jing-yi Yang
Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
Journal of Control Science and Engineering
author_facet Chi-Man Vong
Weng-Fai Ip
Pak-kin Wong
Jing-yi Yang
author_sort Chi-Man Vong
title Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
title_short Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
title_full Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
title_fullStr Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
title_full_unstemmed Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines
title_sort short-term prediction of air pollution in macau using support vector machines
publisher Hindawi Limited
series Journal of Control Science and Engineering
issn 1687-5249
1687-5257
publishDate 2012-01-01
description 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.
url http://dx.doi.org/10.1155/2012/518032
work_keys_str_mv AT chimanvong shorttermpredictionofairpollutioninmacauusingsupportvectormachines
AT wengfaiip shorttermpredictionofairpollutioninmacauusingsupportvectormachines
AT pakkinwong shorttermpredictionofairpollutioninmacauusingsupportvectormachines
AT jingyiyang shorttermpredictionofairpollutioninmacauusingsupportvectormachines
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