Machine Learning Predicts Laboratory Earthquakes - Rouet‐Leduc - 2017 - Geophysical Research Letters - Wiley Online Library

A classical approach to determining that an earthquake may be looming is based on the interevent time (recurrence interval) for characteristic earthquakes, earthquakes that repeat periodically (Schwartz & Coppersmith, 1984). For instance, analysis of turbidite stratigraphy deposited during successive earthquakes dating back 10,000 years suggests that the Cascadia subduction zone is ripe for a megaquake (Goldfinger et al., 2017). The idea behind characteristic, repeating earthquakes was the basis of the well‐known Parkfield prediction based strictly on seismic data. Similar earthquakes occurring between 1857 and 1966 suggested a recurrence interval of 21.9 3.1 years, and thus, an earthquake was expected between 1988 and 1993 (Bakun & Lindh, 1985), but ultimately took place in 2004. With this approach, as earthquake recurrence is not constant for a given fault, event occurrence can only be inferred within large error bounds.