The Short‐Time Prediction of Thermospheric Mass Density Based on Ensemble‐Transfer Learning

• Published in: Space Weather Vol. 21; no. 10
• Main Authors: Wang, Peian, Chen, Zhou, Deng, Xiaohua, Wang, Jing‐Song, Tang, Rongxing, Li, Haimeng, Hong, Sheng, Wu, Zhiping
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.10.2023; Wiley
• Subjects: Accuracy; Aerospace industry; Algorithms; Atmospheric drag; Atmospheric models; Density; Earth orbits; ensemble learning; Low earth orbits; Machine learning; Modelling; NRLMSISE‐00; Satellite data; Satellite orbits; Satellites; short‐time prediction; Space research; thermospheric mass density; transfer learning

Reliable short‐time prediction of thermospheric mass density along the satellite orbit is always essential but challenging for the operation of Low‐Earth orbit satellites. In this paper, three machine‐learning prediction algorithms are investigated, including the Bidirectional Long Short‐Term Memory...