Hybrid seasonal ARIMA and artificial neural network in forecasting southeast asia city air pollutant index
The rise of air pollution has received much attention globally. As an early warning system for air quality control and management, it is important to provide precise future concentrations pollutant information. Using time series forecasting methods, the forecast of daily Air Pollutant Index (API) is...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Academy of Sciences Malaysia
2019
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Online Access: | http://psasir.upm.edu.my/id/eprint/80111/1/Hybrid%20Seasonal%20ARIMA%20and%20Artificial%20Neural%20Network%20in%20Forecasting%20Southeast%20Asia%20City%20Air%20Pollutant%20Index.pdf http://psasir.upm.edu.my/id/eprint/80111/ https://www.akademisains.gov.my/asmsj/article/hybrid-seasonal-arima-and-artificial-neural-network-in-forecasting-southeast-asia-city-air-pollutant-index/ |
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Institution: | Universiti Putra Malaysia |
Language: | English |
Internet
http://psasir.upm.edu.my/id/eprint/80111/1/Hybrid%20Seasonal%20ARIMA%20and%20Artificial%20Neural%20Network%20in%20Forecasting%20Southeast%20Asia%20City%20Air%20Pollutant%20Index.pdfhttp://psasir.upm.edu.my/id/eprint/80111/
https://www.akademisains.gov.my/asmsj/article/hybrid-seasonal-arima-and-artificial-neural-network-in-forecasting-southeast-asia-city-air-pollutant-index/