Revision as of 07:27, 27 May 2019 by WikiSysop (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
CSDMS3.0 - Bridging Boundaries

Machine Learning and Coastal Morphodynamics

Evan Goldstein

University of North Carolina at Greensboro, United States

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 ( and we will respond as soon as possible.

Of interest for:
  • Coastal Working Group
  • Artificial Intelligence & Machine Learning Initiative