Predicting ionospheric precursors before large earthquakes using neural network computing and the potential development of an earthquake early warning system

Jyh-Woei Lin ()
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Jyh-Woei Lin: Nanjing University of Information Science & Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 113, issue 3, No 5, 1519-1542

Abstract: Abstract Total electron content (TEC) precursors of the Chi-Chi Earthquake, which occurred in Taiwan at 01:47:15 on September 21, 1999 (Taiwan Standard Time, TST), with its epicenter at 23.85° N and 120.82° E, a Richter magnitude (ML) of 7.3 (a moment magnitude (Mw) of 7.6), and a focal depth of 8.00 km, were detected 1, 3, and 4 days before the earthquake using two back-propagation neural network (BPNN) models. These results are consistent with the analysis results of Liu et al. (2001) and Lin (2010). Another TEC precursor was detected on May 13, 2003 (TST), 2 days before the earthquake on May 15, 2003 (TST), with an ML of 5.21. Their precursors might be induced by the variations of the geomagnetic and electric fields near their hypocenter. The two BPNN models were to be verified for stability and reliability after performing cross-validation and evaluating the variance in the learning process. For this, the result of the analyzed method can serve as a real-time TEC predicted system for giving any future time as inputs of the two BPNN models. Hence, an earthquake early warning (EEW) system is performable.

Keywords: Total electron content (TEC) precursors; Chi-Chi earthquake; Back-propagation neural network (BPNN); Earthquake early warning (EEW) system (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05356-1

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