The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning
Open accessAbstract
Performance of earthquake early warning systems suffers from false alerts caused by local impulsive noise from natural or anthropogenic sources. To mitigate this problem, we train a generative adversarial network (GAN) to learn the characteristics of first‐arrival earthquake P waves, using 300,000 waveforms recorded in southern California and Japan. We apply the GAN critic as an automatic feature extractor and train a Random Forest classifier with about 700,000 earthquake and noise waveforms. We show that the discriminator can recognize 99.2% of the earthquake P waves and 98.4% of the noise signals. This state‐of‐the‐art performance is expected to reduce significantly the number of false triggers from local impulsive noise. Our study demonstrates that GANs can discover a compact and effective representation of seismic waves, which has the potential for wide applications in seismology.
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Generative Adversarial Networks: An Overview
Creswell, A., White, T., Dumoulin, V., Arulkumaran, K., Sengupta, B., & Bharath, A. A. (2018) · IEEE Signal Processing Magazine · doi:10.1109/msp.2017.2765202 · Cited by 4,540
Convolutional neural network for earthquake detection and location
Perol, T., Gharbi, M., & Denolle, M. (2018) · Science Advances · doi:10.1126/sciadv.1700578 · Cited by 921
Machine Learning Predicts Laboratory Earthquakes
Rouet‐Leduc, B., Hulbert, C., Lubbers, N., Barros, K., Humphreys, C. J., & Johnson, P. A. (2017) · Geophysical Research Letters · doi:10.1002/2017gl074677 · Cited by 420
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Earthquake Early Warning ShakeAlert System: West Coast Wide Production Prototype
Kohler, M. D., Cochran, E. S., Given, D. D., Guiwits, S., Neuhauser, D. S., Henson, I. H., Hartog, R., Bodin, P., Kress, V. C., Thompson, S., et al. (2017) · Seismological Research Letters · doi:10.1785/0220170140 · Cited by 112
Cited by
Applications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491
Machine Learning in Disaster Management: Recent Developments in Methods and Applications
Linardos, V., Drakaki, M., Tzionas, P., & Karnavas, Y. (2022) · Machine Learning and Knowledge Extraction · doi:10.3390/make4020020 · Cited by 319
Metadata
- Authors
- Li, Z., Meier, M., Hauksson, E., Zhan, Z., & Andrews, J.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2018-05-28
- Volume
- 45
- Issue
- 10
- Pages
- 4773-4779
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2799565130
- Cited by
- 305
- References
- 11
- FWCI
- 15.42
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Li, Z., Meier, M., Hauksson, E., Zhan, Z., & Andrews, J. (2018). Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning. Geophysical Research Letters. https://doi.org/10.1029/2018gl077870
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