Publications

Interpretable Machine Learning Tools to Analyze Pm2.5 Sensor Network Data so as to Quantify Local Source Impacts and Long-Range Transport

Benjamin de Foy, Ross Edwards, Khaled Shaifullah Joy, Shahid Uz Zaman, Abdus Salam, James Schauer

Published 2024
Publisher Elsevier BV
DOI 10.2139/ssrn.4860793

Open access (green)

Low-cost sensor networks, data science and forecasting Source apportionment and emission sources Urban and indoor air quality in Dhaka

Cite this

Benjamin de Foy, Ross Edwards, Khaled Shaifullah Joy, Shahid Uz Zaman, Abdus Salam, James Schauer (2024). Interpretable Machine Learning Tools to Analyze Pm2.5 Sensor Network Data so as to Quantify Local Source Impacts and Long-Range Transport. Elsevier BV. https://doi.org/10.2139/ssrn.4860793

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Names in bold are laboratory members. The DOI links to the published paper.