中国空间科学技术

中国空间科学技术 ›› 2025, Vol. 45 ›› Issue (2): 124-132.doi: 10.16708/j.cnki.1000-758X.2025.0030

• 论文 • 上一篇    下一篇

基于数据融合及GA-BP算法的GEO高能电子通量预测

陈建飞，方美华*，吴 康，宋定一，王彪   

  1. 南京航空航天大学 航天学院，南京211100
  • 收稿日期:2023-02-24 修回日期:2024-01-30 录用日期:2024-02-25 发布日期:2025-03-13 出版日期:2025-04-01

GEO high-energy electron flux prediction based on data fusion and GA-BP algorithm

CHEN Jianfei, FANG Meihua*, Wu Kang, Song Dingyi, Wang Biao   

  1. Institute of Aerospace, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China
  • Received:2023-02-24 Revision received:2024-01-30 Accepted:2024-02-25 Online:2025-03-13 Published:2025-04-01

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摘要： 为了提高GEO大于2MeV电子通量提前一天的预测效率，采用基于模拟退火算法和最小二乘拟合的数据融合算法处理GOES系列卫星电子通量数据，以融合后的数据为基础建立遗传算法优化BP神经网络(GA-BP)模型。模型输入参数包括太阳风速度、地磁指数（包括SYM/H、Ap、AU、AE、Dst）、大于0．6MeV电子积分通量和大于2MeV电子积分历史通量，各参数的时间分辨率均为日均值；同时以1999-2007年的数据为训练集，使用数据融合后的GA-BP模型预测2008-2010年的电子积分通量，将预测结果与其他经典模型的预测结果进行比较。结果表明：采用模拟退火算法将位于75°W区域的卫星数据投影到135°W区域，数据误差变小，融合效果更好；大于2MeV电子通量提前1天预测效率为0.863，最高预测效率可达0.931，优于以往很多模型的预测精度。

关键词: GEO卫星, GA-BP算法, 模拟退火算法, 数据融合, 高能电子通量预测, 深层充电

Abstract: In order to improve the prediction efficiency of GEO electron flux greater than 2MeV one day in advance, a data fusion algorithm based on simulated annealing algorithm and least squares fitting was used to process GOES series satellite electron flux data. A genetic algorithm optimized BP neural network (GA-BP) model was established based on the fused data. The input parameters of the model include solar wind speed, geomagnetic index (including SYM/H, Ap, AU, AE, Dst), electron integral flux greater than 0.6MeV, and historical electron integral flux greater than 2MeV. The time resolution of each parameter is daily average; At the same time, using data from 1999 to 2007 as the training set, the GA-BP model after data fusion was used to predict the electron flux from 2008 to 2010, and the predicted results were compared with those of other classical models. The results showed that using simulated annealing algorithm to project satellite data located in the 75°W area to the 135°W area resulted in smaller data errors and better fusion effects; The prediction efficiency of electron flux greater than 2MeV is 0.863 one day in advance, and the highest prediction efficiency can reach 0.931, which is better than the prediction accuracy of many previous models. 

Key words: GEO satellite, GA-BP algorithm, simulated annealing algorithm, Data Fusion, high energy electron flux prediction, Deep charging