Prediction of GPS-TEC on Mw>5 Earthquake Days Using Bayesian Regularization Backpropagation Algorithm
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 Backpropagation Artificial Neural Network Bayesian...
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| Vydáno v: | IEEE geoscience and remote sensing letters Ročník 20; s. 1 |
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01.01.2023
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| Abstract | 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 Backpropagation Artificial Neural Network Bayesian Regularization algorithm is applied to detect the seismic disturbances and anomalies by predicting GPS-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. |
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| AbstractList | 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 Backpropagation Artificial Neural Network Bayesian Regularization algorithm is applied to detect the seismic disturbances and anomalies by predicting GPS-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. |
| Author | Karatay, Secil Gul, Saide Eda |
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| Cites_doi | 10.1162/neco.1992.4.3.415 10.1007/s00190-020-01416-1 10.1109/SIU.2014.6830333 10.1109/TIE.2012.2183833 10.1029/2004RS003061 10.1029/2018GL081251 10.1016/j.asoc.2012.10.014 10.1016/j.spasta.2020.100442 10.1029/2007JA012459 10.1134/S001679321908005X 10.1029/2002JA009605 10.1007/s00521-014-1767-x 10.2174/1874149501509010522 10.3906/elk-1401-57 10.1016/j.asr.2020.01.042 |
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| Snippet | 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... |
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| SubjectTerms | Artificial neural networks Backpropagation Bayes methods Earthquake Earthquakes Ionosphere Neurons Precursor Prediction algorithms Total Electron Content Training |
| Title | Prediction of GPS-TEC on Mw>5 Earthquake Days Using Bayesian Regularization Backpropagation Algorithm |
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