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Development of time series models for various pollutants in Bangalore city using the Akaike information criterion |
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| รหัสดีโอไอ | |
| Creator | 1. Vivekanand Venkataraman 2. Shashank Prasad 3. Balakrishna Aswathanarayana 4. Susmith Barigidad 5. Vinayak Nayak 6. Sai Tarun Kumar N |
| Title | Development of time series models for various pollutants in Bangalore city using the Akaike information criterion |
| Publisher | Faculty of Engineering, Khon Kaen University |
| Publication Year | 2563 |
| Journal Title | Engineering and Applied Science Research |
| Journal Vol. | 47 |
| Journal No. | 3 |
| Page no. | 249-263 |
| Keyword | Time series, Air pollution, Akaike information criterion, ARIMA, Statistics |
| URL Website | https://www.tci-thaijo.org/index.php/easr/index |
| Website title | Engineering and Applied Science Research |
| ISSN | 2539-6161 |
| Abstract | Pollution levels in developing countries,such as India,have become a major source of health problems.They need to be monitoredandcontrolled. Bangalore,one of the major cities in India,facesa huge amount of pollution. Due to the dire need to control these pollutants,a sound mathematical modeling approach needs to be created for forecasting, controlling and monitoring. One such approach is time series modeling. The current workaddresses a time series model that has been developed for the major pollutants in Bangalorecity. Thesepollutants include PM10, PM2.5, NOxand SO2. The models used vary from AR (autoregressive), ARMA (autoregressive moving average) and ARIMA (autoregressive integrated moving average) for modeling air pollution inBangalore city. Additionally,the selection of the best models wasbased on the Akaike Information Criterion, p-value and Box-Pierce test. Various steps were followedto build the model,which includedidentification of missingand extreme values followed by creating an appropriate imputing method and thenidentification of time series models using autocorrelation and partial autocorrelation plots to obtain various time series models. The best time series models werechosen based on the Akaike Information criterion (AIC) and various other statistical tests. |
