Machine learning and its application in seismology
It is an inherently challenging scientific endeavor to understand and predict multi-scale, high-dimensional and nonlinear seismological phenomena. The increasing amount of observational big data breaks the linkage between data collection and interpretation, and increases the obscurity and uncertaint...
| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Reviews of Geophysics and Planetary Physics
2021-01-01
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| Series: | 地球与行星物理论评 |
| Subjects: | |
| Online Access: | https://www.sjdz.org.cn/en/article/doi/10.19975/j.dqyxx.2020-006 |
| _version_ | 1797858676031094784 |
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| author | Xu Yang Yonghua Li Zengxi Ge |
| author_facet | Xu Yang Yonghua Li Zengxi Ge |
| author_sort | Xu Yang |
| collection | DOAJ |
| description | It is an inherently challenging scientific endeavor to understand and predict multi-scale, high-dimensional and nonlinear seismological phenomena. The increasing amount of observational big data breaks the linkage between data collection and interpretation, and increases the obscurity and uncertainty in data analysis. However, there is also artificial intelligent computer technology, i.e. machine learning in the era of big data. The excellent capability of machine learning for implicit relation extraction and complex task processing has enabled it to be applied to a variety of fields. In this article, we introduce some of the commonly used machine learning algorithms in seismology as well as their applications, and discuss the future directions of integrating artificial intelligence with seismic data interpretation. |
| first_indexed | 2024-04-09T21:17:14Z |
| format | Article |
| id | doaj.art-451d0f9106ac434c88340740d7e022a3 |
| institution | Directory Open Access Journal |
| issn | 2097-1893 |
| language | zho |
| last_indexed | 2024-04-09T21:17:14Z |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Reviews of Geophysics and Planetary Physics |
| record_format | Article |
| series | 地球与行星物理论评 |
| spelling | doaj.art-451d0f9106ac434c88340740d7e022a32023-03-28T07:10:51ZzhoEditorial Office of Reviews of Geophysics and Planetary Physics地球与行星物理论评2097-18932021-01-01521768810.19975/j.dqyxx.2020-0062020-006Machine learning and its application in seismologyXu Yang0Yonghua Li1Zengxi Ge2Institute of Geophysics, China Earthquake Administration, Beijing 100081, ChinaInstitute of Geophysics, China Earthquake Administration, Beijing 100081, ChinaSchool of Earth and Space Sciences, Peking University, Beijing 100871, ChinaIt is an inherently challenging scientific endeavor to understand and predict multi-scale, high-dimensional and nonlinear seismological phenomena. The increasing amount of observational big data breaks the linkage between data collection and interpretation, and increases the obscurity and uncertainty in data analysis. However, there is also artificial intelligent computer technology, i.e. machine learning in the era of big data. The excellent capability of machine learning for implicit relation extraction and complex task processing has enabled it to be applied to a variety of fields. In this article, we introduce some of the commonly used machine learning algorithms in seismology as well as their applications, and discuss the future directions of integrating artificial intelligence with seismic data interpretation.https://www.sjdz.org.cn/en/article/doi/10.19975/j.dqyxx.2020-006seismologymachine learningfeature extractiondeep learningneural network |
| spellingShingle | Xu Yang Yonghua Li Zengxi Ge Machine learning and its application in seismology 地球与行星物理论评 seismology machine learning feature extraction deep learning neural network |
| title | Machine learning and its application in seismology |
| title_full | Machine learning and its application in seismology |
| title_fullStr | Machine learning and its application in seismology |
| title_full_unstemmed | Machine learning and its application in seismology |
| title_short | Machine learning and its application in seismology |
| title_sort | machine learning and its application in seismology |
| topic | seismology machine learning feature extraction deep learning neural network |
| url | https://www.sjdz.org.cn/en/article/doi/10.19975/j.dqyxx.2020-006 |
| work_keys_str_mv | AT xuyang machinelearninganditsapplicationinseismology AT yonghuali machinelearninganditsapplicationinseismology AT zengxige machinelearninganditsapplicationinseismology |