GD-CAF: Graph Dual-stream Convolutional Attention Fusion for Precipitation Nowcasting

arXiv:2401.07958v2 Announce Type: replace
Abstract: Accurate precipitation nowcasting is essential for various applications, including flood prediction, disaster management, optimizing agricultural activities, managing transportation routes and renewable energy. While several studies have addressed this challenging task from a sequence-to-sequence perspective, most of them have focused on a single area without considering the existing correlation between multiple disjoint regions. In this paper, we formulate precipitation nowcasting as a spatiotemporal graph sequence nowcasting problem. In particular, we introduce Graph Dual-stream Convolutional Attention Fusion …

abstract applications arxiv attention cs.cv cs.lg disaster disaster management energy flood flood prediction fusion graph management nowcasting perspective precipitation prediction renewable studies them transportation type