Abstract
This article presents the results of applying the method of the minimum area of alarm to the complex forecasting of earthquakes based on data of different types. Point fields of earthquake epicenters and time series of displacements of the earth’s surface, measured using GPS, were used for the prediction. Testing was carried out for earthquakes with a hypocenter depth of up to 60 km for two regions with different seismotectonics: Japan, the forecast time interval from 2016 to 2020, magnitudes \(m \ge 6\); California, the forecast time interval from 2013 to 2020, magnitude \(m \ge 5.5\). Testing has shown the effectiveness of systematic earthquake forecasting using seismological and space geodesy data in combination.
This research was partially funded by Russian Foundation for Basic Research grant number 20-07-00445.
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Gitis, V.G., Derendyaev, A.B., Petrov, K.N. (2021). Earthquake Prediction Based on Combined Seismic and GPS Monitoring Data. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12954. Springer, Cham. https://doi.org/10.1007/978-3-030-86979-3_42
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