A machine learning model developed by researchers at the University of California, Davis (UC Davis) can analyze decades of earthquake data to predict future earthquakes.
The algorithm can determine the probability of a 6.75-magnitude or greater earthquake occurring over a three year-period in a region of California that covers slightly less than 1,000 square kilometers, using records of earthquake since 1970.
The model determined that earthquake data is not as random as previously believed.
The researchers used the number of earthquakes per unit of time and had the model identify patterns in the data.
They also applied statistical techniques used in economics to give recent events greater significance than older ones.
The resulting model provides forecast-like probabilities of earthquakes occurring in a short period of time in the future.
Said UC Davis' John Rundle, "What we've done is show that you can see a regional cycle of activity."
From New Scientist
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