Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction

Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction

Sporadic E (Es) layers in the ionosphere are characterized by intense plasma irregularities in the E region at altitudes of 90–130 km. Because they can significantly influence radio communications and navigation systems, accurate forecasting of Es layers is crucial for ensuring the precision and dep...

Full description

Saved in:
Bibliographic Details
Main Authors: BingKun Yu, PengHao Tian, XiangHui Xue, Christopher J. Scott, HaiLun Ye, JianFei Wu, Wen Yi, TingDi Chen, XianKang Dou
Format: Article
Language:English
Published: Science Press 2025-01-01
Series:Earth and Planetary Physics
Subjects:
ionospheric sporadic e layer
radio occultation
ionosondes
numerical model
deep learning model
artificial intelligence
Online Access:http://www.eppcgs.org/article/doi/10.26464/epp2024048?pageType=en
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.eppcgs.org/article/doi/10.26464/epp2024048?pageType=en

Similar Items