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Rundle, J.B., Donnellan, A., Fox, G. and Crutchfield, J.P. (2022) Nowcasting Earthquakes by Visualizing the Earthquake Cycle with Machine Learning: A Comparison of Two Methods. Surveys in Geophysics, 43, 483-501.
https://doi.org/10.1007/s10712-021-09655-3

has been cited by the following article:

• TITLE: Ambient Noise Tomography, Green’s Function and Earthquakes

  AUTHORS: Panayiotis K. Varotsos, Efthimios S. Skordas

  KEYWORDS: Surface Wave Tomography, Shear Velocity Model, Inversion, Green’s Function, Ambient Noise, Earthquakes

  JOURNAL NAME: International Journal of Geosciences, Vol.13 No.12, December 20, 2022

  ABSTRACT: Green’s function is well-known, among others, in the application of ambient noise tomography methodologies that may demonstrate the potential of hydrocarbon entrapment in the study area. Here it is also shown to be of key importance in identifying the fractal dimension in the unified scaling law for earthquakes as well as in studying an explicit relationship of a future strong earthquake epicenter to the average earthquake potential score. Such studies are now in progress.