Full title: SC26NE04. Machine Learning for Groundwater Science
Instructor(s): Lijing Wang
CEUs: 0.4
Date: Sat., 21 Mar.
Location: Connecticut Convention Center, Hartford, Connecticut, USA
Start Time: 1 p.m.
End Time: 5 p.m.
Description: This half-day course introduces machine learning methods for predicting groundwater levels and explores how machine learning can be integrated with existing numerical models to improve hydrologic forecasting. Participants will learn how to apply Long Short-Term Memory (LSTM) networks for groundwater level prediction, as well as how to develop surrogate models that emulate process-based simulations. The course emphasizes practical applications and is designed to support groundwater research and management under uncertain human and natural disturbances.
By purchasing this item, you are buying a seat for an in-person short course.
Short Courses offer Continuing Education Units (CEUs). One CEU equals 10 hours of participation in an organized continuing education experience under responsible sponsorship, capable direction, and qualified instruction.
Learn more about this and other Northeastern Section Meeting Activities.
For additional information, please contact shortcourse@geosociety.
Product Code: SC26NE04
Product Category: SHORTC