An Urban Air Quality Prediction Model based on Dynamic Correlation of Influencing Factors
Paper
Li, Lin, Mai, Yunqi, Chu, Yu, Tao, Xiaohui and Yong, Jiaming. 2024. "An Urban Air Quality Prediction Model based on Dynamic Correlation of Influencing Factors." N., Shen W.Shen W.Barthes J.-P.Luo J.Qiu T.Zhou X.Zhang J.Zhu H.Peng K.Xu T.Chen (ed.) 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2024 ). Tianjin, China 08 - 10 May 2024 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CSCWD61410.2024.10580204
Paper/Presentation Title | An Urban Air Quality Prediction Model based on Dynamic Correlation of Influencing Factors |
---|---|
Presentation Type | Paper |
Authors | Li, Lin, Mai, Yunqi, Chu, Yu, Tao, Xiaohui and Yong, Jiaming |
Editors | N., Shen W.Shen W.Barthes J.-P.Luo J.Qiu T.Zhou X.Zhang J.Zhu H.Peng K.Xu T.Chen |
Journal or Proceedings Title | Proceedings of the 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2024) |
Journal Citation | pp. 3188-3193 |
Number of Pages | 6 |
Year | 2024 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISBN | 9798350349184 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/CSCWD61410.2024.10580204 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/10580204 |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/10579968/proceeding |
Conference/Event | 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2024 ) |
Event Details | 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2024 ) Parent International Conference on Computer Supported Cooperative Work in Design Delivery In person Event Date 08 to end of 10 May 2024 Event Location Tianjin, China |
Abstract | Urban air quality prediction models can predict pollutant values based on its time series. Existing research shows that the correlation between influencing factors is dynamic. In this paper, we propose an Urban Air Quality Prediction Model based on Dynamic Correlation of Influencing Factors (DynamicAir) to address this problem. In the dynamic correlation module, the dynamic correlation of influencing factors is captured by dynamic graph generation and dynamic graph convolution; in the multi-time-step prediction module, the time correlation of each step and the dynamic correlation of influencing factors are mapped by multi-layer non-linear mapping to obtain the future pollutant concentration values at multi-steps. Experimental results on two real datasets(Beijing Capital International Airport and Beijing Olympic Sports Centre) show that the proposed DynamicAir reduces the RMSE by 1.15% and 4.04% respectively compared to the state-of-the-art baseline model (with a statistical interval of three hours). |
Keywords | air quality prediction |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 460508. Information retrieval and web search |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Wuhan University of Technology, China |
School of Mathematics, Physics and Computing | |
School of Business |
Permalink -
https://research.usq.edu.au/item/z995x/an-urban-air-quality-prediction-model-based-on-dynamic-correlation-of-influencing-factors
32
total views1
total downloads0
views this month0
downloads this month