AI News, Machine-Learning Algorithm Predicts Laboratory Earthquakes

Machine-Learning Algorithm Predicts Laboratory Earthquakes

They've trained a machine-learning algorithm to spot the tell-tale signs that a laboratory earthquake is about to give way using only the sounds it emits under strain.

The team is cautious about the new technique’s utility for real earthquakes, but the work opens up new avenues of research in this area.

Earthquakes occurred here in 1857, 1881, 1901, 1922, 1934, and 1966, suggesting a pattern in which quakes occur every 22 years give or takea few years.

There has been little evidence that this type of prediction will ever be possible, even though there is much anecdotal evidence to suggest that animals can somehow sense the imminent onset of a quake.

At the interface between the blocks, they packed a mixture of rocky material, called gouge material, to simulate the properties of real faults.

Geologists know that as a quake approaches, the gouge material begins to fail, emitting groans and cracks as it shears—a kind of seismic chatter.

It generates lots of small slips and just a few large ones—a distribution that follows the well-known Gutenberg-Richter relation, just as a real earthquakes do.

The question these guys ask is whether the sound emitted by the fault can be used to predict the time of next slip.

The researchers fed the algorithm a sliding window of acoustic emissions, asking it to make a prediction at each instant of the likelihood of an earthquake.

“We show that by listening to the acoustic signal emitted by a laboratory fault, machine learning can predict the time remaining before it fails with great accuracy,” they say.

Rouet-Leduc and co hypothesize that seismic precursors can be much smaller than had previously been thought and so are not usually recorded in the real world.

The machine seems to have spotted an entirely new signal that geologists had previously dismissed as noise in the laboratory quakes.

How to Predict an Earthquake | Dara Ó Briain's Science Club | Brit Lab | BBC

One geo-physicst aims to have sensor networks in every block in Los Angeles and across every fault zone in the world but how? Taken from Dara Ó Briain's ...

What's that Noise?

By listening to the acoustic signal emitted by a laboratory-created earthquake, a computer science approach using machine learning can predict the time ...

Researchers Use Artificial Intelligence To Predict Simulated Earthquakes

Researchers at the Los Alamos National Laboratory in New Mexico have demonstrated that machine-learning technology could play a significant role in ...

NASA scientists predict 99.9% chance of MAJOR Earthquake in California within 2 years

Unnamed Scientists from NASA's Jet Propulsion Lab JPL have come out of the Doom Closet to let everyone know that California is in some major Earthquake ...

Sleuthing Seismic Signals: Understanding Earthquake Hazard and Monitoring Nuclear Explosions

Visit: The probability of a magnitude 6.7 or greater earthquake in the Greater Bay Area during the next 30 years is 63 percent, or about two out ..

Share Your Science: Predicting Earthquakes with Supercomputers

Tom Jordan, Director, Southern California Earthquake at University of Southern California and a team of researchers are using the 27 petaflop Titan ...

How Well Can We Predict Earthquakes?

A string of earthquakes have been occurring in Chile and Southern California. What causes earthquakes, is a bigger one coming, and can we predict them?

Nature's Earthquake Recorders

Massive Alpine Fault earthquakes shake the mud under Lake Christabel.

Earthquake Interaction on the Scale of a Fault to the Planet

Ross Stein (PhD, 1980, Geology), Geophysicist at the United States Geological Survey.

Quakeland: Predicting the Next Big Earthquake Using Machine Learning

Move over haarptards You won'tsee this earthquake prediction or news from dis-info dutchie's magic 3d earthquake crystal ball first. Researchers at Los Alamos ...