Earthquake Footprints for Predicting Events

Abstract

This paper considers the problem of predicting earthquakes. It uses a small amount of information to create a descriptive key that can be used as a footprint to describe an event. A frequency grid clusters events that occurred at the same time and then the algorithm measures the history of these events over preceding days, in particular the gaps when the events did not occur. The clusters with the time gaps can be used to create the footprint description and results suggest that seismic events can in fact be traced using this, and subsequently recognised again, if the same conditions occur. Greek and USA datasets have been looked at and the prediction accuracy can be 70% or better. The author therefore suggests that this is an interesting method that deserves attention.