Raffee, Ahmad Fauzi and Rahmat, Siti Nazahiyah and Abdul Hamid, Hazrul and Jaffar, Muhammad Ismail (2018) A review on short-term prediction of air pollutant concentrations. International Journal of Engineering & Technology, 7 (3.23). pp. 32-35. ISSN 2227-524X
Full text not available from this repository. (Request a copy)Abstract
In the attempt to increase the production of the industrial sector to accommodate human needs; motor vehicles and power plants have led to the decline of air quality. The tremendous decline of air pollution levels can adversely affect human health, especially children, those elderly, as well as patients suffering from asthma and respiratory problems. As such, the air pollution modelling appears to be an important tool to help the local authorities in giving early warning, apart from functioning as a guide to develop policies in near future. Hence, in order to predict the concentration of air pollutants that involves multiple parameters, both artificial neural network (ANN) and principal component regression (PCR) have been widely used, in comparison to classical multivariate time series. Besides, this paper also presents comprehensive literature on univariate time series modelling. Overall, the classical multivariate time series modelling has to be further investigated so as to overcome the limitations of ANN and PCR, including univariate time series methods in short-term prediction of air pollutant concentrations.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Multivariate time series; VAR; air pollution; forecasting |
| Subjects: | T Technology > T Technology (General) T Technology > TD Environmental technology. Sanitary engineering T Technology > TD Environmental technology. Sanitary engineering > TD172-193.5 Environmental pollution |
| Divisions: | Faculty of Civil Engineering and Built Environment > Department of Civil Engineering : Water and Environmental Engineering |
| Depositing User: | UiTM Student Praktikal |
| Date Deposited: | 23 Nov 2021 06:25 |
| Last Modified: | 23 Nov 2021 06:25 |
| URI: | http://eprints.uthm.edu.my/id/eprint/3982 |
Actions (login required)
 |
View Item |