Google’s AI to predict earthquake aftershocks

• Scientists at Harvard University and Google have used an artificial intelligence (AI) system to analyze a database of earthquakes from around the world to predict where aftershocks might occur.

• Earthquakes typically occur in sequences: an initial ‘mainshock’ is often followed by a set of aftershocks.

• Although these aftershocks are usually smaller than the main shock, in some cases, they may significantly hamper recovery efforts.

• Although the timing and size of aftershocks have been understood and explained by established empirical laws, forecasting the location of these events has proven more challenging.

• The team has used a database of information on more than 118 major earthquakes from around the world.

• From there, the team applied a neural net to analyze the relationships between static stress changes caused by the mainshocks and aftershock locations.

• The end result was an improved model to forecast aftershock locations and while this system is still imprecise, it is a motivating step forward.

• Machine learning based forecast may one day help deploy emergency services and inform evacuation plans for areas at risk of an aftershock.

• When the researchers applied neural networks to the data set, they were able to look at the specific combinations of factors that it found important and useful for that forecast, rather than just taking the forecasted results at face value.

• This opens up new possibilities for finding potential physical theories that may allow the better understanding of natural phenomena.

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