Abstract: Forecasting the Daily Hydrological Extremes using Machine Learning methods; Insights from GRACE and Altimetry data (AGU Fall Meeting 2018)

Forecasting the Daily Hydrological Extremes using Machine Learning methods; Insights from GRACE and Altimetry data

Marwa S. Moustafa¹, Ashraf Rateb², Bridget R Scanlon², Alexander Y Sun³ and Himanshu Save⁴, (1)National Authority for Remote Sensing & Space Sciences, Data Reception, Analysis and Receiving Station Affairs, Cairo, Egypt, (2)University of Texas at Austin, Bureau of Economic Geology, Jackson School of Geosciences, Austin, TX, United States, (3)University of Texas at Austin, Bureau of Economic Geology, Austin, United States, (4)The University of Texas at Austin, Center for Space Research, Austin, TX, United States

Back to: Applications of Machine Learning and Data Cubes in Remote Sensing III Posters