Presenters-0428: Difference between revisions
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|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=3RdlIHZsZKE | |CSDMS meeting youtube code=3RdlIHZsZKE | ||
|CSDMS meeting youtube views={{Youtube_3RdlIHZsZKE}} | |||
|CSDMS meeting participants=0 | |CSDMS meeting participants=0 | ||
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Revision as of 16:52, 28 May 2025
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.
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Of interest for:
