Machine Learning Could Improve Earthquake Prediction

A computer program could hold the key to predicting when the next tremors will occur in an earthquake zone. Researchers at the Los Alamos National Laboratory developed an algorithm that demonstrated a high level of accuracy in determining the failure times of quakes simulated in a lab. Here's how the experiment worked. The team analyzed data from a laboratory fault system that contains fault gouge, the ground-up material created by the stone blocks sliding past one another. When a frictional failure occurred in the lab quake, the shearing block moves or displaces, while the gouge material simultaneously dilates and strengthens based on measurably increasing shear stress and friction.