Session 9A AI Applications for Air Quality

Wednesday, 15 January 2020: 1:30 PM-2:30 PM
156A (Boston Convention and Exhibition Center)

CoChair:
Surya Karthik Mukkavilli, Montreal Institute for Learning Algorithms (Mila), Montreal, QC
Papers:
1:30 PM
9A.1
PMNet: Improving Aerosol Predictions using Deep Neural Nets for Limited Ground Stations
Caleb Hoyne, McGill University, Montreal, QC, Canada; and S. K. Mukkavilli and D. Meger

1:45 PM
9A.2
Improving Geophysical Air Quality Forecasts With Machine Learning Algorithms
Hervé Petetin, Barcelona Supercomputing Center, Barcelona, Spain; and A. Soret, M. Guevara, K. Serradell, and C. Pérez García-Pando

2:00 PM
9A.3
Using a Feedforward MLP Neural Network to Fill Gaps in N2O Emission Data
Benjamin Matthew Fehr, University of New Hampshire, Durham, NH; and C. Dorich and R. Conant

2:15 PM
9A.4
Satellite-derived PM2.5 concentrations over South Korea using GOCI aerosol product and a machine learning method
Yeseul Cho, Yonsei University, Seoul, Korea, Republic of (South); and J. Kim, H. Lee, M. Choi, S. Lee, H. Lim, and J. Im

Abstract Submissions Closed



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