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作 者:Jun Zhu Zefeng Li Lihua Fang
机构地区:[1]Laboratory of Seismology and Physics of Earth’s Interior,School of Earth and Space Sciences,University of Science and Technology of China,Hefei 230026,China [2]Mengcheng National Geophysical Observatory,University of Science and Technology of China,Mengcheng 233500,China [3]Institute of Geophysics,China Earthquake Administration,Beijing 100081,China
出 处:《Earthquake Science》2023年第2期95-112,共18页地震学报(英文版)
基 金:the National Key R&D Program of China(No.2021YFC3000700);the Special Fund of the Institute of Geophysics,China Earthquake Administration(Nos.DQJB22X08 and DQJB21Z05).
摘 要:Current popular deep learning seismic phase pickers like PhaseNet and EQTransformer suffer from performance drop in China.To mitigate this problem,we build a unified set of customized seismic phase pickers for different levels of use in China.We first train a base picker with the recently released DiTing dataset using the same U-Net architecture as PhaseNet.This base picker significantly outperforms the original PhaseNet and is generally suitable for entire China.Then,using different subsets of the DiTing data,we fine-tune the base picker to better adapt to different regions.In total,we provide 5 pickers for major tectonic blocks in China,33 pickers for provincial-level administrative regions,and 2 special pickers for the Capital area and the China Seismic Experimental Site.These pickers show improved performance in respective regions which they are customized for.They can be either directly integrated into national or regional seismic network operation or used as base models for further refinement for specific datasets.We anticipate that this picker set will facilitate earthquake monitoring in China.
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