PhaseNet workflow boosts seismic wave detection accuracy

Researchers have developed a new workflow using the PhaseNet machine learning model to improve seismic wave detection on teleseismic data. This workflow, implemented with MsPASS, significantly enhances the recall of P-wave picks by over 700% compared to models trained on regional data. While increasing model size improved accuracy, it drastically reduced inference speed, suggesting GPUs are more suitable than CPUs for scaling this application. AI

IMPACT Improves seismic data analysis accuracy, potentially aiding in earthquake detection and research.

RANK_REASON The cluster contains an academic paper detailing a new methodology and benchmark results for a machine learning model. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• MsPASS
• NVIDIA A100 GPU
• PhaseNet
• USArray Array Network Facility (ANF)

• paper
• other

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