Real-time neural network earthquake profile predictor
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. 17 figs.
- Research Organization:
- University of California
- DOE Contract Number:
- W-7405-ENG-48
- Assignee:
- Univ. of California, Oakland, CA (United States)
- Patent Number(s):
- US 5,490,062/A/
- Application Number:
- PAN: 8-241,060
- OSTI ID:
- 187057
- Country of Publication:
- United States
- Language:
- English
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