[1]WANG Jinhong,JIANG Haikun.Research Progress in Field of Earthquake Prediction by Machine Learning Based on Seismic Data[J].Journal of Seismological Research,2023,46(02):173-187.[doi:10.20015/j.cnki.ISSN1000-0666.2023.0022
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Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume:
46
Number of periods:
2023 02
Page number:
173-187
Column:
Public date:
2023-03-10
- Title:
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Research Progress in Field of Earthquake Prediction by Machine Learning Based on Seismic Data
- Author(s):
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WANG Jinhong1; JIANG Haikun2
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(1.Institute of Earthquake Forecasting,China Earthquake Administration,Beijing 100036,China)(2.China Earthquake Networks Center,Beijing 100045,China)
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- Keywords:
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earthquake prediction; machine learning; feature extraction; model evaluation
- CLC:
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P315.7
- DOI:
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10.20015/j.cnki.ISSN1000-0666.2023.0022
- Abstract:
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Machine learning's prominent implicit feature extraction and complex task processing capabilities are driving the science of earthquake prediction.In order to systematically understand the development status of machine learning technology in the field of earthquake prediction,this paper focuses on the application of machine learning in the field of earthquake prediction at home and abroad in recent years from the three aspects of earthquake magnitude prediction,earthquake location and earthquake occurrence time estimation in a specified time-space window,among which AI is the most widely used in earthquake magnitude prediction.In addition,this paper summarizes the main characteristic parameters,models and evaluation related issues of machine learning earthquake prediction,and explores the influence of seismicity parameters on earthquake prediction results from various evaluation mechanisms.Finally,a preliminary discussion and outlook on the problems existing in the field of earthquake prediction will be conducted.In the foreseeable future,the introduction of AI technology and the expansion of application fields are likely to lead the continuous development of the field of earthquake prediction.