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首页|期刊导航|地球空间信息科学学报(英文版)|An optimized BP neural network for modeling zenith tropospheric delay in the Chinese mainland using coupled particle swarm and genetic algorithm

An optimized BP neural network for modeling zenith tropospheric delay in the Chinese mainland using coupled particle swarm and genetic algorithm

Liangke Huang Haohang Bi Hongxing Zhang Shitai Wang Fasheng Liao Lilong Liu Weiping Jiang

地球空间信息科学学报(英文版)2025,Vol.28Issue(4):中插25,1927-1942,17.
地球空间信息科学学报(英文版)2025,Vol.28Issue(4):中插25,1927-1942,17.DOI:10.1080/10095020.2024.2392701

An optimized BP neural network for modeling zenith tropospheric delay in the Chinese mainland using coupled particle swarm and genetic algorithm

An optimized BP neural network for modeling zenith tropospheric delay in the Chinese mainland using coupled particle swarm and genetic algorithm

Liangke Huang 1Haohang Bi 2Hongxing Zhang 3Shitai Wang 2Fasheng Liao 4Lilong Liu 2Weiping Jiang5

作者信息

  • 1. College of Geomatics and Geoinformation,Guilin University of Technology,Guilin,China||State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology,CAS,Wuhan,China
  • 2. College of Geomatics and Geoinformation,Guilin University of Technology,Guilin,China
  • 3. State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology,CAS,Wuhan,China
  • 4. Heze Earthquake Monitoring Center,Shandong Earthquake Agency,Heze,China
  • 5. GNSS Research Center,Wuhan University,Wuhan,China
  • 折叠

摘要

关键词

Zenith tropospheric delay/PSO algorithm/GABP neural network/ERA5 reanalysis data/GPT3 model

Key words

Zenith tropospheric delay/PSO algorithm/GABP neural network/ERA5 reanalysis data/GPT3 model

引用本文复制引用

Liangke Huang,Haohang Bi,Hongxing Zhang,Shitai Wang,Fasheng Liao,Lilong Liu,Weiping Jiang..An optimized BP neural network for modeling zenith tropospheric delay in the Chinese mainland using coupled particle swarm and genetic algorithm[J].地球空间信息科学学报(英文版),2025,28(4):中插25,1927-1942,17.

基金项目

This work is supported by Guangxi Natural Science Foundation of China[grant numbers 2023GXNSFAA026434 and 2023GXNSFAA026355] ()

State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology,Chinese Academy of Sciences[grant num-ber SKLGED2023-3-1] ()

Innovation Project of Guangxi Graduate Education[grant number YCSW2023338] ()

and the"Ba Gui Scholars"program of the provincial govern-ment of Guangxi. ()

地球空间信息科学学报(英文版)

1009-5020

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