The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Machine Learning Approaches to Model Sea Turtle Nesting: A Comparison of Random Forest and Support Vector Machine Models (AGU25)

Machine Learning Approaches to Model Sea Turtle Nesting: A Comparison of Random Forest and Support Vector Machine Models

Angelina Scamardo1, Halie Wetherington2, Samantha Seals1 and Phillip P Schmutz2, (1)University of West Florida, Mathematics and Statistics, Pensacola, United States, (2)University of West Florida, Earth and Environmental Sciences, Pensacola, United States