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LS+Informer in Polar Motion Prediction
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Dandan WANG1, Shubo QIAO1, *, Dongliang CHENG1, Hailong XU2, Yaming YAN1
Journal of Geodesy and Geodynamics | 2025, 45(9) : 899 - 904
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Journal of Geodesy and Geodynamics | 2025, 45(9): 899-904
LS+Informer in Polar Motion Prediction
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Dandan WANG1, Shubo QIAO1, *, Dongliang CHENG1, Hailong XU2, Yaming YAN1
Affiliations
  • 1 School of Surveying and Mapping, Information Engineering University, 62 Kexue Road, Zhengzhou 450001, China
  • 2 31121 Troops, Nanjing 210042, China

    • WANG Dandan, majors in spatial geodesy and navigation positioning, E-mail:

About Author:

WANG Dandan, majors in spatial geodesy and navigation positioning, E-mail:

Published: 2025-09-15 doi: 10.14075/j.jgg.2024.10.487
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In order to improve the medium and long term prediction accuracy of polar motion, the LS+Informer(least-squares extrapolation and Informer, LS+Informer) prediction model is proposed based on the traditional LS+AR prediction model combined with deep learning method. The mean absolute error(MAE) was used as the evaluation index based on LS+AR forecast model and Bulletin A forecast results. After LS+Informer method is adopted, the medium and long term prediction accuracy of PMX and PMY components of polar motion can be significantly improved, and the amplitude can reach 61.94% and 64.86% respectively. At the same time, the MAE value can be controlled within 10 mas in the medium and long term 365-day phase. The results show that the prediction accuracy of LS+Informer model is better than that of LS+AR model, and better than that of Bulletin A. The results demonstrate that the LS+Informer model can be effectively used in medium and long term polar motion prediction.

Transformer model  /  Informer model  /  LS+AR model  /  polar motion  /  MAE
王丹丹, 乔书波, 程栋梁, 徐海龙, 闫亚明. LS+Informer用于极移预报的方法研究. 大地测量与地球动力学, 2025 , 45 (9) : 899 -904 . DOI: 10.14075/j.jgg.2024.10.487
Dandan WANG, Shubo QIAO, Dongliang CHENG, Hailong XU, Yaming YAN. LS+Informer in Polar Motion Prediction[J]. Journal of Geodesy and Geodynamics, 2025 , 45 (9) : 899 -904 . DOI: 10.14075/j.jgg.2024.10.487
Funding
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  • National Natural Science Foundation of China(42474043)
Appendix
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Year 2025 volume 45 Issue 9
29
10
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Article Info
doi: 10.14075/j.jgg.2024.10.487
  • Receive Date：2024-10-25
  • Online Date：2026-10-29
  • Published：2025-09-15
Article Data
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History
  • Received：2024-10-25
Funding
National Natural Science Foundation of China(42474043)
Affiliations
    1 School of Surveying and Mapping, Information Engineering University, 62 Kexue Road, Zhengzhou 450001, China
    2 31121 Troops, Nanjing 210042, China
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https://castjournals.cast.org.cn/joweb/ddcl/EN/10.14075/j.jgg.2024.10.487
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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