LSTM based forecasting of the next day's values of ionospheric total electron content (TEC) as an earthquake precursor signal

The sudden vibrations that occur due to the fractures in the Earth's crust, spreading in waves and shaking the Earth's surface, are natural disaster that causes significant loss of life and property. To take measures against these destructive effects, it is important to be able to forecast the occurrence time of an earthquake in advance. However, although earthquake experts can forecast which fault line the next earthquake may occur on by monitoring the movements in the fault lines, they cannot accurately forecast the exact timing. Detection of earthquake precursor signals a few days before the earthquake has become an increasingly popular field of interest. Strong correlations have been observed between earthquakes and ionospheric parameters in recent years. Total Electron Content (TEC) is an important parameter that can be affected by seismic activity in ionospheric studies and has been investigated as a potential earthquake precursor by many researchers. It has been observed that earthquakes cause significant disturbances and changes in TEC values, which are one of the ionospheric parameters. The ability to identify earthquake precursor signals before an earthquake occurs is critically important for earthquake detection. We evaluate the performance of the proposed approach using GPS-TEC data obtained from numerous ground-based GPS stations in earthquake-prone regions of Turkey, Italy, Japan, and China. In this study, TEC values in six different regions where earthquakes with Mw > 5.6 occurred were forecasted one day before the earthquake using LSTM. The results showed that the LSTM model achieved an R-square (R-2) value of at least 0.9982 and the root mean square error (RMSE) value of at most 0.2302 for all experimental earthquake days used. The proposed approach may be useful for monitoring ionospheric anomalies and potentially developing an early warning system for earthquakes.