A Dual-Prediction Framework for High-Energy Proton Flux Driven by Graph Neural Networks

Predicting high-energy proton flux is essential for radiation-effect protection of satellite devices. We introduce a dual-prediction framework based on Graph Neural Networks (GNN) to model proton flux from both non-time-series and time-series perspectives. In the non-time-series approach, the model...

Deskribapen osoa

Xehetasun bibliografikoak

Egile Nagusiak:	Jia Qiao, Xiaoning Yang, Yuming Liu, Yenan Liu, Yaping Cheng
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	IEEE 2025-01-01
Saila:	IEEE Access
Gaiak:	Proton flux prediction graph neural networks
Sarrera elektronikoa:	https://ieeexplore.ieee.org/document/11214361/
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!