Photo from wikipedia
The detection of earthquake precursor signals a few days before the earthquake day is one of the most studied subjects today. In recent years, a strong correlation is observed between… Click to show full abstract
The detection of earthquake precursor signals a few days before the earthquake day is one of the most studied subjects today. In recent years, a strong correlation is observed between earthquakes and ionospheric parameters. In this study, a feed-forward back propagation artificial neural network (ANN) Bayesian regularization (BR) algorithm is applied to detect the seismic disturbances and anomalies by predicting global positioning system (GPS)-total electron content (TEC) on earthquake days with magnitude greater than 5. It is observed that TEC is predicted with greater error margins for the stations at a maximum distance of 50 km from the epicenters. The errors for earthquakes less than Mw 7 are smaller than those for greater than 7.
Journal Title: IEEE Geoscience and Remote Sensing Letters
Year Published: 2023
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!