Diverse Explorations of Rainfall Nowcasting with TrajGRU: Mitigating Smoothness and Fading Out Challenges for Longer Lead Times

Machine learning models offer promising potential in precipitation nowcasting. However, a common issue faced by many of these models is the tendency to produce blurry precipitation nowcasts, which are unrealistic. Previous research on the deep learning model - TrajGRU (Shi et al., 2017) indicated that data imbalance in radar images and the...

Machine Learning Aided Reliability Analysis for Spatially Varying Slopes in 2D and 3D

The Random Finite Element Method (RFEM) is a robust stochastic method for slope reliability analysis that incorporates the spatial variability of soil properties. However, the extensive computational time associated with the direct Monte Carlo simulation limits its practical application. To overcome this problem, this study investigates the use...