Rural Research Summary: Machine Learning Models скачать в хорошем качестве

Rural Research Summary: Machine Learning Models

The University of Guelph is home to a wide diversity of research on rural people, places, and environments. As a leader in rural research, this video series facilitates knowledge sharing across rural Ontario and beyond.  This video highlights recent research titled “Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed,” published in the Journal of Environmental Management. Conducted by Ahmed Elsayed, Sarah Rixon, Jana Levison, Andrew Binns, and Pradeep Goel, the research examines how machine learning tools can improve predictions of nutrient levels in surface water, offering practical insights to support farmers, planners, policy makers, and community organizations in managing agricultural watersheds more effectively. This rural research summary was created through the Connecting the Dots initiative. To learn more about the initiative and access other rural research summaries please visit http://www.rural.uoguelph.ca.