Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction
摘要
关键词
ionospheric sporadic E layer/radio occultation/ionosondes/numerical model/deep learning model/artificial intelligence分类
天文与地球科学引用本文复制引用
BingKun Yu,PengHao Tian,XiangHui Xue,Christopher JScott,HaiLun Ye,JianFei Wu,Wen Yi,TingDi Chen,XianKang Dou..Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction[J].Earth and Planetary Physics,2025,9(1):P.10-19,10.基金项目
supported by the Project of Stable Support for Youth Team in Basic Research Field,CAS(grant No.YSBR-018) (grant No.YSBR-018)
the National Natural Science Foundation of China(grant Nos.42188101,42130204) (grant Nos.42188101,42130204)
the B-type Strategic Priority Program of CAS(grant no.XDB41000000) (grant no.XDB41000000)
the National Natural Science Foundation of China(NSFC)Distinguished Overseas Young Talents Program,Innovation Program for Quantum Science and Technology(2021ZD0300301) (NSFC)
the Open Research Project of Large Research Infrastructures of CAS-“Study on the interaction between low/mid-latitude atmosphere and ionosphere based on the Chinese Meridian Project”.The project was supported also by the National Key Laboratory of Deep Space Exploration(Grant No.NKLDSE2023A002) (Grant No.NKLDSE2023A002)
the Open Fund of Anhui Provincial Key Laboratory of Intelligent Underground Detection(Grant No.APKLIUD23KF01) (Grant No.APKLIUD23KF01)
the China National Space Administration(CNSA)pre-research Project on Civil Aerospace Technologies No.D010305,D010301. (CNSA)