Presenters-0428: Difference between revisions
From CSDMS
(Created page with "{{Presenters temp |CSDMS meeting event title=CSDMS3.0 - Bridging Boundaries |CSDMS meeting event year=2019 |CSDMS meeting presentation type=Invited oral presentation |CSDMS me...") |
No edit summary |
||
Line 13: | Line 13: | ||
{{Presenters presentation | {{Presenters presentation | ||
|CSDMS meeting abstract presentation=Numerical modeling is at the core of prediction in coastal settings. Observational data is used in tandem with models for a variety of modeling tasks, but the perhaps the coupling could be tighter? I will discuss a range of Machine Learning tools that co-workers and I have integrated with coastal morphodynamic models that allow for a tight coupling of models and data, and provide morphodynamic insight. | |CSDMS meeting abstract presentation=Numerical modeling is at the core of prediction in coastal settings. Observational data is used in tandem with models for a variety of modeling tasks, but the perhaps the coupling could be tighter? I will discuss a range of Machine Learning tools that co-workers and I have integrated with coastal morphodynamic models that allow for a tight coupling of models and data, and provide morphodynamic insight. | ||
|CSDMS meeting youtube code= | |CSDMS meeting youtube code=3RdlIHZsZKE | ||
|CSDMS meeting participants=0 | |CSDMS meeting participants=0 | ||
}} | }} |
Latest revision as of 07:27, 27 May 2019
CSDMS3.0 - Bridging Boundaries
Machine Learning and Coastal Morphodynamics
Abstract
Numerical modeling is at the core of prediction in coastal settings. Observational data is used in tandem with models for a variety of modeling tasks, but the perhaps the coupling could be tighter? I will discuss a range of Machine Learning tools that co-workers and I have integrated with coastal morphodynamic models that allow for a tight coupling of models and data, and provide morphodynamic insight.
Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.
Of interest for: