江西科学2025，Vol.43Issue(1)：52-58,210,8.DOI:10.13990/j.issn1001-3679.2025.01.007
基于iInformer的电离层TEC短期预测
Short-Term Prediction of Ionospheric TEC Based on iInformer
摘要
Abstract
The monitoring and prediction of total ionospheric electron content(TEC)is an important aspect of near-Earth space environment research,which is of great significance for satellite communication and navigation positioning.This article proposes a new method for short-term prediction of TEC in the Chinese regional ionosphere using the Transformer-based iInformer model,and predicts the ionosphere during geomagnetic period and storm periods respectively.In order to analyze the predictive performance of the new short-term ionospheric model,comparisons were made with the PatchTST model,Dlinear models,and long short-term memory(LSTM)models.The results show that the iInformer model within the selected area of magnetostatic period is effectively applicable to short-term prediction tasks and the accuracy of predicting TEC is significantly better than other comparative models,with RMSE(Root mean square error)below 1.4 TECU(total electron content units)in all three regions.The iInformer model can maintain stable predictive performance when dealing with different data volumes.Notably,when the number of datasets is relatively limited(less than two months),the forecasting accuracy of the iInformer model is significantly better than other models.Compared to a single data source,the iInformer model under multiple data sources has significantly improved prediction accuracy,with an improvement range from 2%to 7.4%.关键词
电离层总电子数(TEC)/Transformer/iInformer/线性模型/磁静期/磁暴期Key words
total number of ionospheric electrons(TEC)/transformer/iInformer/linear model/geomagnetic period/geomagnetic storm period分类
天文与地球科学引用本文复制引用
田晓鹏,罗亦泳,张紫怡..基于iInformer的电离层TEC短期预测[J].江西科学,2025,43(1):52-58,210,8.基金项目
江西省自然科学基金项目(20202BABL204070). （20202BABL204070）
