Shaking up Seismology: Data Mining for Earthquake Detection
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چکیده
Seismic sensors collect massive quantities of data that contain a wealth of information about processes within the earth. Seismologists are increasingly adopting data mining and machine learning techniques to identify previously unknown earthquakes in large seismic data sets. Our new earthquake detection method, Fingerprint and Similarity Thresholding (FAST), enables waveform-similarity-based earthquake detection in long duration continuous seismic data by leveraging locality sensitive hashing, a data mining technique for efficiently identifying similar items in large data sets. Ongoing research into waveform feature representations and detection over a seismic network will be presented.
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