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摘要:
PhaseNet and EQTransformer are two state-of-the-art earthquake detection methods that have been increasingly applied worldwide.To evaluate the generaliz-ation ability of the two models and provide insights for the development of new models,this study took the sequences of the Yunnan Yangbi M6.4 earthquake and Qinghai Maduo M7.4 earthquake as examples to compare the earthquake detection effects of the two abovementioned models as well as their abilities to process dense seismic sequences.It has been demonstrated from the corresponding research that due to the differences in seismic waveforms found in different geographical regions,the picking performance is reduced when the two models are applied directly to the detection of the Yangbi and Maduo earthquakes.PhaseNet has a higher recall than EQTransformer,but the recall of both models is reduced by 13%-56%when compared with the results rep-orted in the original papers.The analysis results indicate that neural networks with deeper layers and complex structures may not necessarily enhance earthquake detection perfor-mance.In designing earthquake detection models,attention should be paid to not only the balance of depth,width,and architecture but also to the quality and quantity of the training datasets.In addition,noise datasets should be incorporated during training.According to the continuous waveforms detected 21 days before the Yangbi and Maduo earthquakes,the Yangbi earthquake exhibited foreshock,while the Maduo earthquake showed no foreshock activity,indicating that the two earthquakes'nucleation processes were different.
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篇名 Comparison of the earthquake detection abilities of PhaseNet and EQTransformer with the Yangbi and Maduo earthquakes
来源期刊 地震学报(英文版) 学科
关键词
年,卷(期) 2021,(5) 所属期刊栏目
研究方向 页码范围 425-435
页数 11页 分类号
字数 语种 英文
DOI 10.29382/eqs-2021-0038
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期刊影响力
地震学报(英文版)
双月刊
1674-4519
11-5695/P
16开
北京民族学院南路5号(北京8116信箱)
1980
eng
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1366
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0
总被引数(次)
3070
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