Real-time neural network earthquake profile predictor
Abstract
A neural network has been developed that uses first-arrival energy to predict the characteristics of impending earthquake seismograph signals. The propagation of ground motion energy through the earth is a highly nonlinear function. This is due to different forms of ground motion as well as to changes in the elastic properties of the media throughout the propagation path. The neural network is trained using seismogram data from earthquakes. Presented with a previously unseen earthquake, the neural network produces a profile of the complete earthquake signal using data from the first seconds of the signal. This offers a significant advance in the real-time monitoring, warning, and subsequent hazard minimization of catastrophic ground motion.
- Inventors:
-
- Castro Valley, CA
- Issue Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- OSTI Identifier:
- 870284
- Patent Number(s):
- 5490062
- Assignee:
- Regents of University of California (Oakland, CA)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01V - GEOPHYSICS
- DOE Contract Number:
- W-7405-ENG-48
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- real-time; neural; network; earthquake; profile; predictor; developed; first-arrival; energy; predict; characteristics; impending; seismograph; signals; propagation; ground; motion; earth; highly; nonlinear; function; due; forms; changes; elastic; properties; media; throughout; path; trained; seismogram; data; earthquakes; previously; unseen; produces; complete; signal; offers; significant; advance; monitoring; warning; subsequent; hazard; minimization; catastrophic; neural network; significant advance; time monitoring; real-time monitoring; elastic properties; neural net; /702/706/
Citation Formats
Leach, Richard R, and Dowla, Farid U. Real-time neural network earthquake profile predictor. United States: N. p., 1996.
Web.
Leach, Richard R, & Dowla, Farid U. Real-time neural network earthquake profile predictor. United States.
Leach, Richard R, and Dowla, Farid U. Mon .
"Real-time neural network earthquake profile predictor". United States. https://www.osti.gov/servlets/purl/870284.
@article{osti_870284,
title = {Real-time neural network earthquake profile predictor},
author = {Leach, Richard R and Dowla, Farid U},
abstractNote = {A neural network has been developed that uses first-arrival energy to predict the characteristics of impending earthquake seismograph signals. The propagation of ground motion energy through the earth is a highly nonlinear function. This is due to different forms of ground motion as well as to changes in the elastic properties of the media throughout the propagation path. The neural network is trained using seismogram data from earthquakes. Presented with a previously unseen earthquake, the neural network produces a profile of the complete earthquake signal using data from the first seconds of the signal. This offers a significant advance in the real-time monitoring, warning, and subsequent hazard minimization of catastrophic ground motion.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 1996},
month = {Mon Jan 01 00:00:00 EST 1996}
}