Abstract
基于分析时间序列数据的门限控制单元（GRU）神经网络模型，利用电离层TEC网格点历史数据、太阳活动指数、地磁活动指数作为预测因子，提出一种高精度电离层TEC格点预测模型.对全球60个网格点的数据进行了模型预测和对比实验，得到北半球平均相对精度的均值为83.96%，高于南半球的73.60%，表明预测模型在北半球的适应性更好，且中低纬地区的适应性优于高纬地区；预测模型在磁扰动期的平均相对精度的均值比磁平静期平均相对精度的均值高，约1.95%；与基于递归神经网络（RNN）、长短时记忆网络（LSTM）和双向长短时记忆网络（Bi-LSTM）的电离层TEC单站预测模型相比，本文预测模型的均方根误差（RMSE）平均为原来的80.8%.
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