FIELD: seismology.
SUBSTANCE: invention relates to seismology and can be used for selection of focal zones of potential earthquakes. Essence: according to seismic tomography and gravimetric data in the same nodes of the spatial grid covering the investigated region, models of velocities of transverse seismic waves and density are constructed. Space velocities of transverse seismic waves and density from nodes of the regular grid to hypocenters of past earthquakes are spatially interpolated. Shift modulus is calculated from values of velocities of transverse seismic waves and density in nodes of spatial grid, as well as hypocenters of past earthquakes. Artificial neural network "with teacher" is trained. Neural network input is geographic coordinates of hypocenters of past earthquakes and values of shear modulus calculated in them, and magnitude of output is magnitude of corresponding earthquakes. Then, using the trained artificial neuron network, the probable magnitudes of potential earthquakes are predicted in the nodes of the spatial grid which covers the considered volume of the medium.
EFFECT: technical result is determination of probable magnitudes of potential earthquakes.
1 cl, 1 tbl, 7 dwg
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Authors
Dates
2020-08-21—Published
2019-12-09—Filed