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Air Quality Station Simulation via LSTM and Attention-Based Modelling

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Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and control the mechanisms that determine air quality, cities deploy networks of measurement stations, and launch initiatives for collecting denser data about the concentration of pollutants in the atmosphere.

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arXiv AI
Aug 11

AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting

arXiv:2608. 09775v1 Announce Type: new Abstract: Accurate air quality forecasting is essential for public health and urban environmental management, but remains challenging because pollutant channels differ in periodicity and distribution drift, while their concentration trajectories contain both multi-scale dependencies and rapid changes.

By Fan Yang, Nan Chen, Yijie Dong, Yuchen Zhang, Wei Zhang