Multi-Pollutant Ground-level Air Pollution Prediction through Deep MeteoGCN-ConvLSTM

Author:

Muthukumar Pratyush1,Pathak Shaurya1,Nagrecha Kabir1,Hosseini Hirad1,Comer Dawn2,Amini Navid1,Holm Jeanne2,Pourhomayoun Mohammad1

Affiliation:

1. California State University Los Angeles,Department of Computer Science,Los Angeles,CA

2. City of Los Angeles,Los Angeles,CA

Publisher

IEEE

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Estimation of Surface-Level NO2 Using Satellite Remote Sensing and Machine Learning: A review;IEEE Geoscience and Remote Sensing Magazine;2024

2. Using Deep Learning for Spatial and Temporal Analysis of Wildfire Start and Progression;2023 International Conference on Computational Science and Computational Intelligence (CSCI);2023-12-13

3. Predicting Atmospheric Air Pollution: A Convolutional- Transformer Approach for Spatial and Temporal Analysis of PM2.5;2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE);2023-07-24

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