Generalized earthquake classification
Ben Lasscock
Video: https://youtu.be/uT0Nkf0BA7o
Abstract
We characterize the source of an earthquake based on identifying
the nodal lines of the radiation pattern it produces. These
characteristics are the mode of failure of the rock (shear or
tensile), the orientation of the fault plane and direction of
slip. We will also derive a correlation coefficient comparing the
source mechanisms of different earthquakes. The problem is
formulated in terms of a simple binary classification on the
surface of the sphere. Our design goal was to derive an algorithm
that would be both robust to misclassification of the observed data
and suitable for online processing. We will then go on to derive a
mapping which translates the learned solution for the separating
hyper-plane back to the physics of the problem, that is, the
probable source type and orientation. For reproducibility, we will
demonstrate our algorithm using the example data provided with the
HASH earthquake classification software, which is available online.
machine learning, earthquake, hazard, classification.
DOI10.25080/Majora-629e541a-003