
Machine Learning Predicts Laboratory Earthquakes - sizzle
http://onlinelibrary.wiley.com/doi/10.1002/2017GL074677/full
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dane-pgp
Why look at "laboratory earthquakes" when we have plenty of data about actual
earthquakes? We sort of accept that after a big earthquake, there is likely to
be smaller earthquakes nearby and a short time later. By looking at all the
available data on all the major and minor earthquakes in a region over time,
I'm sure there would be other patterns found, even if the predictive power is
not actionable.

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candiodari
Really ? Where can I download long term acoustic data from earthquake fault
lines ? Needs to be years, and ideally including more than a few real
earthquakes (let's say 50 to 100 of them would be ideal).

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dane-pgp
I didn't mean acoustic data, but I was thinking of long term global datasets
like this:

[http://www.isc.ac.uk/iscgem/overview.php](http://www.isc.ac.uk/iscgem/overview.php)

It covers over 26,000 earthquakes going back roughly a century, but I admit
I'm somewhat disappointed that it only seems to cover Magnitude Mw ≥ 5.5
quakes.

A machine learning algorithm may need even more data points than that to spot
reasonable patterns, even if it was given the location of landmasses and fault
lines to help it, but I wouldn't be surprised if someone could generate a
model which can predict future quakes at least somewhat better than random
chance (factoring in averages for a given location).

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candiodari
That's just locations and quakes. And even there, only really big ones. That's
only half of what you need to predict quakes.

There's not much in that dataset to predict with.

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thisisit
So predicting earth in a controlled environment, something which might have
been generated using a pseudo random generator code? How will this hold up in
nature?

