Better Detection of Earthquakes with Machine Learning

New work in the space using Machine Learning, we had proposed related methods when studying neural models.  Here a convolutional neural network.

Researchers Create Earthquake System Model with Better Detection Capabilities  in CACM

University of Wyoming,  October 12, 2021

The University of Wyoming's Pejman Tahmasebi and Tao Bai have invented a machine learning (ML) model that boosts the accuracy of earthquake detection significantly over current models. Tahmasebi said the model processes signal data recorded by seismometers, and can automatically distinguish seismic events from seismic noise. The model combines existing long short-term memory and fully convolutional network ML models; the former captures data signal changes over time, and the latter filters out hidden features of seismic events. Tahmasebi said the model boasts 89.1% classification accuracy, a 14.5% improvement over the state-of-the-art ConvNetQuake model.

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