Application of Sample-Compressed Neural Network and Adaptive-Clustering Algorithm for Magnetotelluric Inverse Modeling
文献类型：期刊论文
| 作者 | Liu, Weiqiang3,4; Lu, Qingtian2; Yang, Liangyong1; Lin, Pinrong2; Wang, Zhihui2 |
| 刊名 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
 |
| 出版日期 | 2021-09-01 |
| 卷号 | 18期号:9页码:1540-1544 |
| ISSN号 | 1545-598X |
| 关键词 | Machine learning algorithms Neural networks Clustering algorithms Discrete cosine transforms Training Image coding Geology Artificial neural networks (ANNs) clustering methods geophysical image processing geophysics |
| DOI | 10.1109/LGRS.2020.3005796 |
| 英文摘要 | In this letter, two machine learning algorithms are improved, including a sample-compressed neural network algorithm for magnetotelluric (MT) inversion and an adaptive-clustering analysis algorithm for boundary demarcation. MT is widely used in deep geological structure exploration; however, data processing and interpretation still need to be further improved. Inverting the underground electrical structure model from the surface electromagnetic response is a highly nonlinear optimization problem. Common quasi-linear algorithms rely on the initial model and are easy to converge to a local minimum. In addition, demarcating the boundary and attributes of the abnormal bodies according to the inversion results is often manual, inefficient, and haphazard. The validity of the above two machine learning methods is proved by using the simulated data and the actual data. The new algorithms can improve the efficiency and automation of MT data inversion imaging. |
| WOS关键词 | 3-D INVERSION |
| 资助项目 | Basic Scientific Research Funds of the Chinese Academy of Geological Sciences[JKY1725] ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources[KLGEPT201908] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000690441200014 |
| 资助机构 | Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Basic Scientific Research Funds of the Chinese Academy of Geological Sciences ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources ; Key Laboratory of Geophysical Electromagnetic Probing Technologies of Ministry of Natural Resources |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/102616]  |
| 专题 | 中国科学院地质与地球物理研究所 |
| 通讯作者 | Lu, Qingtian |
| 作者单位 | 1.Chinese Acad Sci IGGCAS, Inst Geol & Geophys, Beijing 100029, Peoples R China 2.Chinese Acad Geol Sci, Beijing, Peoples R China 3.Chinese Acad Geol Sci, Inst Geophys & Geochem Explorat, Key Lab Geophys Electromagnet Probing Technol, Minist Nat Resources, Langfang 065000, Peoples R China 4.China Univ Petr Cup, Coll Geophys, Beijing 102249, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Weiqiang,Lu, Qingtian,Yang, Liangyong,et al. Application of Sample-Compressed Neural Network and Adaptive-Clustering Algorithm for Magnetotelluric Inverse Modeling[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2021,18(9):1540-1544. |
| APA | Liu, Weiqiang,Lu, Qingtian,Yang, Liangyong,Lin, Pinrong,&Wang, Zhihui.(2021).Application of Sample-Compressed Neural Network and Adaptive-Clustering Algorithm for Magnetotelluric Inverse Modeling.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,18(9),1540-1544. |
| MLA | Liu, Weiqiang,et al."Application of Sample-Compressed Neural Network and Adaptive-Clustering Algorithm for Magnetotelluric Inverse Modeling".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 18.9(2021):1540-1544. |
入库方式： OAI收割
来源：地质与地球物理研究所
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