Short-term forecast of ionospheric sporadic E intensity fusing physical parameters via deep learning

Tianyang Hu; Xiaohua Xu; Jia Luo; Haifeng Liu

doi:10.1007/s10291-025-01947-0

Short-term forecast of ionospheric sporadic E intensity fusing physical parameters via deep learning

Tianyang Hu, Xiaohua Xu, Jia Luo, Haifeng Liu

Geospace Frontiers

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	198
Journal	GPS Solutions
Volume	29
Issue number	4
DOIs	https://doi.org/10.1007/s10291-025-01947-0
State	Published - Sep 18 2025

Keywords

Deep learning
Global navigation satellite system
Ionospheric sporadic E layer
Radio occultation

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10.1007/s10291-025-01947-0

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title = "Short-term forecast of ionospheric sporadic E intensity fusing physical parameters via deep learning",

keywords = "Deep learning, Global navigation satellite system, Ionospheric sporadic E layer, Radio occultation",

author = "Tianyang Hu and Xiaohua Xu and Jia Luo and Haifeng Liu",

year = "2025",

month = sep,

day = "18",

doi = "10.1007/s10291-025-01947-0",

language = "English",

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T1 - Short-term forecast of ionospheric sporadic E intensity fusing physical parameters via deep learning

AU - Hu, Tianyang

AU - Xu, Xiaohua

AU - Luo, Jia

AU - Liu, Haifeng

PY - 2025/9/18

Y1 - 2025/9/18

KW - Deep learning

KW - Global navigation satellite system

KW - Ionospheric sporadic E layer

KW - Radio occultation

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M3 - Article

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VL - 29

JO - GPS Solutions

JF - GPS Solutions

IS - 4

M1 - 198

ER -

Short-term forecast of ionospheric sporadic E intensity fusing physical parameters via deep learning

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