Abstract:According to nonlinear and nonstationary characteristics of ionospheric TEC, we establish a residual correction ionospheric prediction model based on the combination of Prophet and Elman neural network. The model is used to model and forecast the ionospheric TEC time series provided by IGS during different degrees of solar activity. The results show that the modified model can reflect the variation characteristics of ionospheric TEC. The average relative accuracy of the model in low solar activity years and high solar activity years is 92.9% and 92.2%, and the root mean square error is 0.94 TECu and 1.77 TECu, respectively. The accuracy of the modified model is significantly higher than that of the Prophet-Elman model and the single Elman model.
HUANG Jiawei,LU Tieding,HE Xiaoxing et al. Short Term Prediction Model of Ionospheric TEC Based on Residual Correction of Prophet-Elman[J]. jgg, 2021, 41(8): 783-788.