Effective PM2.5 concentration forecasting based on multiple spatial–temporal GNN for areas without monitoring stations

Author:

Su I-FangORCID,Chung Yu-ChiORCID,Lee Chiang,Huang Pin-Man

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference58 articles.

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4. Self-adaptive spatial-temporal network based on heterogeneous data for air quality prediction;Chang;Connection Science,2020

5. Cheng, W., Shen, Y., Zhu, Y., & Huang, L. (2018). A neural attention model for urban air quality inference: Learning the weights of monitoring stations. In 32nd AAAI conference on artificial intelligence (pp. 2151–2158).

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