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AGU A028 Combining Physical Simulation - Notícia OVGA 09-08-2017

Physical Simulation and Geophysical Sciences – AGU: A028

Notícia OVGA – 09/08/2017

Nota: No fim desta notícia encontra-se um resumo em português.


Session ID#: 26710

Session Description:

Simulation of Physical processes through solution of differential equations, or mechanistic models, serves as a core tool of geophysical studies. In contrast to this cause and effect-driven Physical Simulation (PS), Machine Learning (ML) models instantiate pattern recognition techniques ad often operate as a black box. A key question is how to combine PS and ML solutions to advance understanding of the physical system and improve the PS. This session is seeking cross-disciplinary presentations that demonstrate applied combiations of PS and ML. Examples may include data assimilation (where ML may drive the design of PS), using ML to filter PS outputs, use of PS to develop training data sets for ML and ML approaches to classification of large scale PS outputs. Demonstrations of practical applications are strongly encouraged.

Primary Convener: Sean A McKenna, IBM Ireland, Dublin, Ireland

Conveners: Ronni Grapenthin, New Mexico Institute of Mining and Technology, Socorro, NM, United States, Anna Michalak, Carnegie Institution of Science, Global Ecology, Washington, United States and Markus Reichstein, Max-Planck Institute of Biogeochemistry, Department of Biogeochemical Integraion, Jena, Germany

Co-Organized with:

Atmospheric Sciences, Biogeosciences, Hydrology, and Seismology


B – Biogeosciences

H – Hydrology

S – Seismology

Index Terms:

0430 Computational methods and data processing[BIOGEOSCIENCES]

1816 Estimation and forecasting[HYDROLOGY]

3315 Data assimilation[Atmospheric Processes]

7212 Earthquake ground motions and engineering




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