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CREDIT-X1local:A reference dataset for machine learning seismology from ChinArray in Southwest China

Earthquake Science 2024年第2期37卷 139-157页

作者： Lu Li Weitao Wang Ziye Yu Yini Chen Institute of Geophysics China Earthquake AdministrationBeijing 100081China Key Laboratory of Earthquake Source physics China Earthquake AdministrationBeijing 100081China Zhejiang Earthquake Agency HangzhouZhejiang 310013China

High-quality datasets are critical for the development of advanced machine-learning algorithms in ***,we present an earthquake dataset based on the ChinArray phase I records(X1).ChinArray phase I was deployed in the southern north-south seismic zone(20°N-32°N,95°E-110°E)in 2011-2013 using 355 portable broadband seismic ***-X1local,the first release of the ChinArray Reference Earthquake Dataset for Innovative Techniques(CREDIT),includes comprehensive information for the 105,455 local events that occurred in the southern north-south seismic zone during array observation,incorporating them into a single HDF5 *** 100-Hz sampled three-component waveforms are organized by event for stations within epicenter distances of 1,000 km,and records of≥200 s are included for each *** types of phase labels are *** first includes manually picked labels for 5,999 events with magnitudes≥2.0,providing 66,507 pg,42,310 Sg,12,823 pn,and 546 Sn *** second contains automatically labeled phases for 105,442 events with magnitudes of−1.6 to *** phases were picked using a recurrent neural network phase picker and screened using the corresponding travel time curves,resulting in 1,179,808 pg,884,281 Sg,176,089 pn,and 22,986 Sn ***,first-motion polarities are included for 31,273 pg *** event and station locations are provided,so that deep learning networks for both conventional phase picking and phase association can be trained and *** CREDIT-X1local dataset is the first million-scale dataset constructed from a dense seismic array,which is designed to support various multi-station deep-learning methods,high-precision focal mechanism inversion,and seismic tomography ***,owing to the high seismicity in the southern north-south seismic zone in China,this dataset has great potential for future scientific discoveries.

关键词： earthquake dataset machine learning pg/Sg/pn/Sn phase picking p-wave first-motion polarity

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