An advanced deep learning predictive model for air quality index forecasting with remote satellite-derived hydro-climatological variables
Article
Article Title | An advanced deep learning predictive model for air quality index forecasting with remote satellite-derived hydro-climatological variables |
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ERA Journal ID | 3551 |
Article Category | Article |
Authors | Ahmed, Abul Abrar Masrur, Jui, S. Janifer Jabin, Sharma, Ekta, Ahmed, Mohammad Hafez, Raj, Nawin and Bose, Aditi |
Journal Title | Science of the Total Environment |
Journal Citation | 906 |
Article Number | 167234 |
Number of Pages | 19 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0048-9697 |
1879-1026 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.scitotenv.2023.167234 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0048969723058618 |
Abstract | Forecasting the air quality index (AQI) is a critical and pressing challenge for developing nations worldwide. With air pollution emerging as a significant threat to the environment, this study considers seven study sites of the sub-tropical region in Bangladesh and introduces a novel hybrid deep-learning model. The proposed model, expressed as CLSTM-BiGRU, integrates a convolutional neural network (CNN), a long-short term memory (LSTM), and a bi-directional gated recurrent unit (BiGRU) network. Leveraging nineteen remotely sensed predictor variables and harnessing the grey wolf optimization (GWO) algorithm, the CLSTM-BiGRU model showcases its superiority in air quality forecasting. It consistently outperforms the benchmark models, yielding lower forecasting errors and higher efficiency (i.e., correlation coefficient |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 410599. Pollution and contamination not elsewhere classified |
370102. Air pollution processes and air quality measurement | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Melbourne |
Academic Registrar's Office | |
School of Mathematics, Physics and Computing | |
West Virginia University, United States |
https://research.usq.edu.au/item/z28v5/an-advanced-deep-learning-predictive-model-for-air-quality-index-forecasting-with-remote-satellite-derived-hydro-climatological-variables
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