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Quality influencing factors of dispersion curves from short period dense arrays based on a convolutional neural network across the north section of the Xiaojiang fault area

Si Chen Rui Gao Zhanwu Lu Yao Liang Wei Cai Lifu Cao Zilong Chen Guangwen Wang

地震学报（英文版）2023，Vol.36Issue(3)：200-211,12.
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地震学报（英文版）2023，Vol.36Issue(3)：200-211,12.

Quality influencing factors of dispersion curves from short period dense arrays based on a convolutional neural network across the north section of the Xiaojiang fault area

Quality influencing factors of dispersion curves from short period dense arrays based on a convolutional neural network across the north section of the Xiaojiang fault area

Si Chen 1Rui Gao 2Zhanwu Lu 1Yao Liang 1Wei Cai 1Lifu Cao 1Zilong Chen 1Guangwen Wang1

作者信息

  • 1. Institute of Geology,Chinese Academy of Geological Sciences,Beijing 100037,China||SinoProbe Laboratory of Ministry of Natural Resources,Beijing 100037,China
  • 2. Institute of Geology,Chinese Academy of Geological Sciences,Beijing 100037,China||State Key Laboratory of Tibetan Plateau Earth System,Environment and Resources(TPESER),Beijing 100101,China||SinoProbe Laboratory of Ministry of Natural Resources,Beijing 100037,China||School of Earth Sciences and Engineering,Sun Yat-Sen University,Guangzhou 510275,China
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摘要

关键词

convolutional neural network/ambient noise tomography/dispersion curve

Key words

convolutional neural network/ambient noise tomography/dispersion curve

引用本文复制引用

Si Chen,Rui Gao,Zhanwu Lu,Yao Liang,Wei Cai,Lifu Cao,Zilong Chen,Guangwen Wang..Quality influencing factors of dispersion curves from short period dense arrays based on a convolutional neural network across the north section of the Xiaojiang fault area[J].地震学报（英文版）,2023,36(3):200-211,12.

基金项目

This study was financially supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0701),the Fund from the Key Laboratory of Deep-Earth Dynamics of the Ministry of Natural Resources(No.J1901-38),the National Natural Science Foundation of China(Nos.42174121 and 91962109),and the China Geological Survey Project(No.DD20190001). （STEP）

地震学报（英文版）

1000-9116

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