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A Deep Neural Network to identify foreshocks in real time
November 26, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
K. Vikraman
arXiv ID
1611.08655
Category
physics.geo-ph
Cross-listed
cs.LG
Citations
9
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Foreshock events provide valuable insight to predict imminent major earthquakes. However, it is difficult to identify them in real time. In this paper, I propose an algorithm based on deep learning to instantaneously classify a seismic waveform as a foreshock, mainshock or an aftershock event achieving a high accuracy of 99% in classification. As a result, this is by far the most reliable method to predict major earthquakes that are preceded by foreshocks. In addition, I discuss methods to create an earthquake dataset that is compatible with deep networks.
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