Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Because small changes in atmospheric and surface conditions can have large, difficult-to-predict effects on future weather, traditional weather forecasts are released only about 10 days in advance. A ...

Meteorologists and other environmental scientists rely on numerical forecast models to aid in developing a weather outlook. These models, such as the American GFS model and European ECMWF model, use ...

When supply chain practitioners think about forecasting, they focus on demand forecasting. Demand forecasting is essential, but the number of different forecasts that an effective organization should ...

Successful test results of a new machine learning (ML) technique developed at Georgia Tech could help communities prepare for extreme weather and coastal flooding. The approach could also be applied ...