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A Novel Time–Frequency Similarity Method for P-Wave First-Motion Polarity Detection [PDF]
SensorsP-wave first-motion polarity is a critical parameter for determining earthquake focal mechanisms. Extracting relative P-wave arrival times and polarity information using waveform cross-correlation techniques can enhance the accuracy of earthquake ...
Yanji Yao +4 more
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Applied Sciences, 2023 P-wave first-motion polarity is important for the inversion of earthquake focal mechanism solutions. The focal mechanism solution can further contribute to our understanding of the source rupture process, the fault structure, and the regional stress ...
Shuai Li +5 more
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P-wave first-motion polarity determination of waveform data in western Japan using deep learning [PDF]
Earth, Planets and Space, 2019 P-wave first-motion polarity is the most useful information in determining the focal mechanisms of earthquakes, particularly for smaller earthquakes.
Shota Hara +2 more
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Acoustic emission features and P-wave first-motion polarity of tensile fractures in the rock
工程科学学报, 2022 To investigate the acoustic emission (AE) characteristics of tensile fracture in the rock, an AE experiment of granite, marble, and red sandstone using an expanding agent for fracture generation was designed.
Xi-ling LIU +4 more
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Detection and Monitoring of Mining-Induced Seismicity Based on Machine Learning and Template Matching: A Case Study from Dongchuan Copper Mine, China [PDF]
SensorsThe detection and monitoring of mining-induced seismicity are essential for understanding the mechanisms behind earthquakes and mitigating seismic hazards.
Tao Wu, Zhikun Liu, Shaopeng Yan
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Reliability of Focal Mechanism Solutions for Small and Medium Earthquakes Based on Different Methods
Taiyuan Ligong Daxue xuebao, 2022 Three representative small and medium earthquakes in Shanxi seismic belt in recent years were taken as examples. By using different methods, such as the first motion of P-wave, first motion of P-wave combining P/SV/SH amplitude ratio, CAP (Cut and Past),
Penghu GUAN +4 more
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Earthquake Science, 2023 In recent years, artificial intelligence technology has exhibited great potential in seismic signal recognition, setting off a new wave of research. Vast amounts of high-quality labeled data are required to develop and apply artificial intelligence in ...
Ming Zhao +3 more
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PolarCAP – A deep learning approach for first motion polarity classification of earthquake waveforms
Artificial Intelligence in Geosciences, 2022 The polarity of first P-wave arrivals plays a significant role in the effective determination of focal mechanisms specially for smaller earthquakes. Manual estimation of polarities is not only time-consuming but also prone to human errors.
Megha Chakraborty +6 more
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P Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning [PDF]
Journal of Geophysical Research: Solid Earth, 2018 AbstractDetermining earthquake hypocenters and focal mechanisms requires precisely measured P wave arrival times and first‐motion polarities. Automated algorithms for estimating these quantities have been less accurate than estimates by human experts, which are problematic for processing large data volumes.
Zachary E. Ross +2 more
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Frontiers in Earth Science, 2023 Accurate P-wave first-motion-polarity (FMP) information can contribute to solving earthquake focal mechanisms, especially for small earthquakes, to which waveform-based methods are generally inapplicable due to the computationally expensive high ...
Ming Zhao +8 more
doaj +1 more source