HyMePre: A Spatial–Temporal Pretraining Framework with Hypergraph Neural Networks for Short-Term Weather Forecasting

HyMePre: A Spatial–Temporal Pretraining Framework with Hypergraph Neural Networks for Short-Term Weather Forecasting

Accurate short-term weather forecasting plays a vital role in disaster response, agriculture, and energy management, where timely and reliable predictions are essential for decision-making. Graph neural networks (GNNs), known for their ability to model complex spatial structures and relational data,...

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Bibliographic Details
Main Authors: Fei Wang, Dawei Lin, Baojun Chen, Guodong Jing, Yi Geng, Xudong Ge, Daoming Wei, Ning Zhang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
weather forecasting
graph neural network
hypergraph
pretraining
Online Access:https://www.mdpi.com/2076-3417/15/15/8324
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