3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China
The bedrock beneath the Tengger Desert is covered by Quaternary deposits, making it difficult to directly observe the underlying geological information using traditional geological methods. In areas with limited prior geological information, employing geophysical methods to obtain deep-seated inform...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2023.1235468/full |
| _version_ | 1797774953796337664 |
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| author | Yulong Dong Yulong Dong Yang Liu Wuxu Peng Yansi Chen Junjie Fan Xiaobing Huang Huilong Liu Qiang Sun |
| author_facet | Yulong Dong Yulong Dong Yang Liu Wuxu Peng Yansi Chen Junjie Fan Xiaobing Huang Huilong Liu Qiang Sun |
| author_sort | Yulong Dong |
| collection | DOAJ |
| description | The bedrock beneath the Tengger Desert is covered by Quaternary deposits, making it difficult to directly observe the underlying geological information using traditional geological methods. In areas with limited prior geological information, employing geophysical methods to obtain deep-seated information, constructing a multi-source geophysical dataset, and performing three-dimensional modeling can significantly enhance our understanding of the underground geological structures. Cluster analysis is a fundamental unsupervised machine learning technique employed in data mining to investigate the data structure within the feature space. This paper proposes an iterative weighted distance-based extension to the k-means clustering algorithm, referred to as the Iterative Weighted Distance K-means (IW k-means++) algorithm. It incorporates the farthest distance method to select the initial centroid, performs iterative centroid updates based on weighted distance, and dynamically adjusts feature weights during training. The Davies-Bouldin index shows that the performance of IW k-means ++ clustering algorithm is better than the traditional K-Meme ++ clustering algorithm in 3D pseudo-lithology modeling. |
| first_indexed | 2024-03-12T22:28:42Z |
| format | Article |
| id | doaj.art-6a55d2aec45947de8bd58efe75643f8e |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-03-12T22:28:42Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-6a55d2aec45947de8bd58efe75643f8e2023-07-21T19:21:53ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632023-07-011110.3389/feart.2023.123546812354683D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, ChinaYulong Dong0Yulong Dong1Yang Liu2Wuxu Peng3Yansi Chen4Junjie Fan5Xiaobing Huang6Huilong Liu7Qiang Sun8Center for Geophysical Survey, China Geological Survey, Langfang, ChinaSchool of Earth Sciences and Resources, China University of Geosciences, Beijing, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaCenter for Geophysical Survey, China Geological Survey, Langfang, ChinaThe bedrock beneath the Tengger Desert is covered by Quaternary deposits, making it difficult to directly observe the underlying geological information using traditional geological methods. In areas with limited prior geological information, employing geophysical methods to obtain deep-seated information, constructing a multi-source geophysical dataset, and performing three-dimensional modeling can significantly enhance our understanding of the underground geological structures. Cluster analysis is a fundamental unsupervised machine learning technique employed in data mining to investigate the data structure within the feature space. This paper proposes an iterative weighted distance-based extension to the k-means clustering algorithm, referred to as the Iterative Weighted Distance K-means (IW k-means++) algorithm. It incorporates the farthest distance method to select the initial centroid, performs iterative centroid updates based on weighted distance, and dynamically adjusts feature weights during training. The Davies-Bouldin index shows that the performance of IW k-means ++ clustering algorithm is better than the traditional K-Meme ++ clustering algorithm in 3D pseudo-lithology modeling.https://www.frontiersin.org/articles/10.3389/feart.2023.1235468/fullpseudo-lithology modelingIW k-means++multi-source geophysical datasetsoverlay areagravity magneto telluric joint inversion |
| spellingShingle | Yulong Dong Yulong Dong Yang Liu Wuxu Peng Yansi Chen Junjie Fan Xiaobing Huang Huilong Liu Qiang Sun 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China Frontiers in Earth Science pseudo-lithology modeling IW k-means++ multi-source geophysical datasets overlay area gravity magneto telluric joint inversion |
| title | 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China |
| title_full | 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China |
| title_fullStr | 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China |
| title_full_unstemmed | 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China |
| title_short | 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China |
| title_sort | 3d pseudo lithologic modeling via iterative weighted k means algorithm from tengger desert cover area china |
| topic | pseudo-lithology modeling IW k-means++ multi-source geophysical datasets overlay area gravity magneto telluric joint inversion |
| url | https://www.frontiersin.org/articles/10.3389/feart.2023.1235468/full |
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