A Deep Learning-Based Electromagnetic Signal for Earthquake Magnitude Prediction
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The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, China
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School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China
3
School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
4
Engineering Department, Shenzhen MSU-BIT University, Shenzhen 518172, China
*
Author to whom correspondence should be addressed.
Academic Editors: Filippo Costa and Ali Khenchaf
Sensors 2021, 21(13), 4434; https://doi.org/10.3390/s21134434
Received: 8 April 2021
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Revised: 18 June 2021
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Accepted: 24 June 2021
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Published: 28 June 2021
(This article belongs to the Section Electronic Sensors)
The influence of earthquake disasters on human social life is positively related to the magnitude and intensity of the earthquake, and effectively avoiding casualties and property losses can be attributed to the accurate prediction of earthquakes. In this study, an electromagnetic sensor is investigated to assess earthquakes in advance by collecting earthquake signals. At present, the mainstream earthquake magnitude prediction comprises two methods. On the one hand, most geophysicists or data analysis experts extract a series of basic features from earthquake precursor signals for seismic classification. On the other hand, the obtained data related to earth activities by seismograph or space satellite are directly used in classification networks. This article proposes a CNN and designs a 3D feature-map which can be used to solve the problem of earthquake magnitude classification by combining the advantages of shallow features and high-dimensional information. In addition, noise simulation technology and SMOTE oversampling technology are applied to overcome the problem of seismic data imbalance. The signals collected by electromagnetic sensors are used to evaluate the method proposed in this article. The results show that the method proposed in this paper can classify earthquake magnitudes well.
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MDPI and ACS Style
Bao, Z.; Zhao, J.; Huang, P.; Yong, S.; Wang, X. A Deep Learning-Based Electromagnetic Signal for Earthquake Magnitude Prediction. Sensors 2021, 21, 4434. https://doi.org/10.3390/s21134434
AMA Style
Bao Z, Zhao J, Huang P, Yong S, Wang X. A Deep Learning-Based Electromagnetic Signal for Earthquake Magnitude Prediction. Sensors. 2021; 21(13):4434. https://doi.org/10.3390/s21134434
Chicago/Turabian StyleBao, Zhenyu, Jingyu Zhao, Pu Huang, Shanshan Yong, and Xin’an Wang. 2021. "A Deep Learning-Based Electromagnetic Signal for Earthquake Magnitude Prediction" Sensors 21, no. 13: 4434. https://doi.org/10.3390/s21134434
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