CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor
Air quality; Carbon monoxide; Deterioration; Forecasting; Health risks; Long short-term memory; Air pollutants; Air quality levels; Ambient air; Carbon monoxide concentration; Deep learning; Empirical Mode Decomposition; Forecasting and air quality; Heart disease; Human health; Urban areas; Empirica...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-270262023-05-29T17:38:49Z CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor Zaini N. Ean L.W. Ahmed A.N. Chow M.F. Malek M.A. 56905328500 55324334700 57214837520 57214146115 55636320055 Air quality; Carbon monoxide; Deterioration; Forecasting; Health risks; Long short-term memory; Air pollutants; Air quality levels; Ambient air; Carbon monoxide concentration; Deep learning; Empirical Mode Decomposition; Forecasting and air quality; Heart disease; Human health; Urban areas; Empirical mode decomposition Deterioration of air quality levels due to the high concentration of air pollutants in ambient air, especially within urban areas, has severely affected human health. Constant exposure to a dangerous air pollutant of carbon monoxide (CO) may lead to serious health problems such as heart diseases, lung damage and respiratory system failure, which may increase mortality risk. Therefore, this study aims to forecast CO concentration in urban areas in Malaysia using a hybrid deep learning model. Empirical mode decomposition (EMD) is used to decompose CO concentration data into multiple components, namely intrinsic mode functions (IMFs) and a residual. Attention-based long short-term memory (ALSTM), the combination of multiple LSTM layers and an attention layer, is used to forecast the decomposed components individually. Then, the forecasted sub-sequences are accumulated to obtain the final forecasting of CO concentration. In this study, forecasting CO concentration is based on hourly historical time series data considering the effect of meteorological parameters. EMD-ALSTM outperforms individual LSTM and ALSTM models in terms of statistical evaluation analysis. The results indicate that the hybrid forecasting model has successfully forecasted CO concentration with reliable accuracy. � 2022 IEEE. Final 2023-05-29T09:38:48Z 2023-05-29T09:38:48Z 2022 Conference Paper 10.1109/ICDI57181.2022.10007246 2-s2.0-85146994627 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146994627&doi=10.1109%2fICDI57181.2022.10007246&partnerID=40&md5=6709aa47a19a2754d7960e725647ff51 https://irepository.uniten.edu.my/handle/123456789/27026 53 56 Institute of Electrical and Electronics Engineers Inc. Scopus |
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| description |
Air quality; Carbon monoxide; Deterioration; Forecasting; Health risks; Long short-term memory; Air pollutants; Air quality levels; Ambient air; Carbon monoxide concentration; Deep learning; Empirical Mode Decomposition; Forecasting and air quality; Heart disease; Human health; Urban areas; Empirical mode decomposition |
| author2 |
56905328500 |
| author_facet |
56905328500 Zaini N. Ean L.W. Ahmed A.N. Chow M.F. Malek M.A. |
| format |
Conference Paper |
| author |
Zaini N. Ean L.W. Ahmed A.N. Chow M.F. Malek M.A. |
| spellingShingle |
Zaini N. Ean L.W. Ahmed A.N. Chow M.F. Malek M.A. CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| author_sort |
Zaini N. |
| title |
CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| title_short |
CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| title_full |
CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| title_fullStr |
CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| title_full_unstemmed |
CO concentration forecasting with attention-based LSTM and EMD for urban areas in Selangor |
| title_sort |
co concentration forecasting with attention-based lstm and emd for urban areas in selangor |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806426591300943872 |