Dual-channel spatial–temporal difference graph neural network for PM$$_{2.5}$$ forecasting
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-08036-0.pdf
Reference40 articles.
1. Guan W-J, Zheng X-Y, Chung KF, Zhong N-S (2016) Impact of air pollution on the burden of chronic respiratory diseases in China: time for urgent action. The Lancet 388(10054):1939–1951. https://doi.org/10.1016/S0140-6736(16)31597-5
2. Wang S, Li Y, Zhang J, Meng Q, Meng L, Gao F (2020) Pm2.5-gnn: A domain knowledge enhanced graph neural network for pm2.5 forecasting. In: Proceedings of the 28th international conference on advances in geographic information systems. SIGSPATIAL ’20, pp 163–166. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3397536.3422208
3. Qi Y, Li Q, Karimian H, Liu D (2019) A hybrid model for spatiotemporal forecasting of pm2.5 based on graph convolutional neural network and long short-term memory. Sci Total Environ 664:1–10. https://doi.org/10.1016/j.scitotenv.2019.01.333
4. Sun W, Sun J (2017) Daily pm2.5 concentration prediction based on principal component analysis and lssvm optimized by cuckoo search algorithm. J Environ Manage 188:144–152. https://doi.org/10.1016/j.jenvman.2016.12.011
5. Lin Y, Mago N, Gao Y, Li Y, Chiang Y-Y, Shahabi C, Ambite JL (2018) Exploiting spatiotemporal patterns for accurate air quality forecasting using deep learning. In: Proceedings of the 26th ACM SIGSPATIAL international conference on advances in geographic information systems. SIGSPATIAL ’18, pp 359–368. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3274895.3274907
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