摘要
Seismology is a data-intensive and data-driven science.The rapid growth of seismometer density and data size calls for more efficient and effective processing tools.In recent years,artificial intelligence(AI)has been increasingly used in various areas of seismology.Among them,earthquake monitoring is likely the one most impacted(Kong QK et al.,2019;Mousavi and Beroza,2022).Popular seismic phase picking models and workflows like PhaseNet,EQTransformer,RISP,PALM,LOC-FLOW,QUAKE-FLOW(Zhu WQ and Beroza,2019;Mousavi et al.,2020;Liao SR et al.,2021;Zhou YJ et al.,2021;Zhang M et al.,2022;Zhu WQ et al.,2023)have been proposed and widely used.Also,AI algorithms for association(Ross et al.,2019;Yu ZY and Wang WT,2022),polarity determination and focal mechanism inversion(Ross et al.,2018;Zhang J et al.,2023;Li S et al.,2023),earthquake discrimination(Li ZF et al.,2018;Linville et al.,2019;Miao FJ et al.,2020)have emerged.
