A new multiple-factor clustering method considering both box fractal dimension and orientation of joints
The paper proposes a new multiple-factor clustering method (NMFCM) with consideration of both box fractal dimension (BFD) and orientation of joints. This method assumes that the BFDs of different clusters were uneven, and clustering was performed by redistributing the joints near the boundaries of c...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-04-01
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| Series: | Journal of Rock Mechanics and Geotechnical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674775521001372 |
| _version_ | 1828876711496777728 |
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| author | Tiexin Liu Annan Jiang Jianhui Deng Jun Zheng Zhenghu Zhang |
| author_facet | Tiexin Liu Annan Jiang Jianhui Deng Jun Zheng Zhenghu Zhang |
| author_sort | Tiexin Liu |
| collection | DOAJ |
| description | The paper proposes a new multiple-factor clustering method (NMFCM) with consideration of both box fractal dimension (BFD) and orientation of joints. This method assumes that the BFDs of different clusters were uneven, and clustering was performed by redistributing the joints near the boundaries of clusters on a polar map to maximize an index for estimating the difference of the BFD (DBFD). Three main aspects were studied to develop the NMFCM. First, procedures of the NMFCM and reasonableness of assumptions were illustrated. Second, main factors affecting the NMFCM were investigated by numerical simulations with disk joint models. Finally, two different sections of a rock slope were studied to verify the practicability of the NMFCM. The results demonstrated that: (1) The NMFCM was practical and could effectively alleviate the problem of hard boundary during clustering; (2) The DBFD tended to increase after the improvement of clustering accuracy; (3) The improvement degree of the NMFCM clustering accuracy was mainly influenced by three parameters, namely, the number of clusters, number of redistributed joints, and total number of joints; and (4) The accuracy rate of clustering could be effectively improved by the NMFCM. |
| first_indexed | 2024-12-13T08:27:25Z |
| format | Article |
| id | doaj.art-f7375d6c8e334890bee3d2915c6c231f |
| institution | Directory Open Access Journal |
| issn | 1674-7755 |
| language | English |
| last_indexed | 2024-12-13T08:27:25Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Rock Mechanics and Geotechnical Engineering |
| spelling | doaj.art-f7375d6c8e334890bee3d2915c6c231f2022-12-21T23:53:52ZengElsevierJournal of Rock Mechanics and Geotechnical Engineering1674-77552022-04-01142366376A new multiple-factor clustering method considering both box fractal dimension and orientation of jointsTiexin Liu0Annan Jiang1Jianhui Deng2Jun Zheng3Zhenghu Zhang4Department of Civil Engineering, Dalian Maritime University, Dalian, 116026, ChinaDepartment of Civil Engineering, Dalian Maritime University, Dalian, 116026, China; Corresponding author.State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, ChinaDepartment of Civil Engineering, Zhejiang University, Hangzhou, 310058, ChinaState Key Laboratory of the Coastal and Offshore Engineering, School of Civil Engineering, Dalian University of Technology, Dalian, 116024, ChinaThe paper proposes a new multiple-factor clustering method (NMFCM) with consideration of both box fractal dimension (BFD) and orientation of joints. This method assumes that the BFDs of different clusters were uneven, and clustering was performed by redistributing the joints near the boundaries of clusters on a polar map to maximize an index for estimating the difference of the BFD (DBFD). Three main aspects were studied to develop the NMFCM. First, procedures of the NMFCM and reasonableness of assumptions were illustrated. Second, main factors affecting the NMFCM were investigated by numerical simulations with disk joint models. Finally, two different sections of a rock slope were studied to verify the practicability of the NMFCM. The results demonstrated that: (1) The NMFCM was practical and could effectively alleviate the problem of hard boundary during clustering; (2) The DBFD tended to increase after the improvement of clustering accuracy; (3) The improvement degree of the NMFCM clustering accuracy was mainly influenced by three parameters, namely, the number of clusters, number of redistributed joints, and total number of joints; and (4) The accuracy rate of clustering could be effectively improved by the NMFCM.http://www.sciencedirect.com/science/article/pii/S1674775521001372Joint clusteringBox fractal dimension (BFD)OrientationHard boundary |
| spellingShingle | Tiexin Liu Annan Jiang Jianhui Deng Jun Zheng Zhenghu Zhang A new multiple-factor clustering method considering both box fractal dimension and orientation of joints Journal of Rock Mechanics and Geotechnical Engineering Joint clustering Box fractal dimension (BFD) Orientation Hard boundary |
| title | A new multiple-factor clustering method considering both box fractal dimension and orientation of joints |
| title_full | A new multiple-factor clustering method considering both box fractal dimension and orientation of joints |
| title_fullStr | A new multiple-factor clustering method considering both box fractal dimension and orientation of joints |
| title_full_unstemmed | A new multiple-factor clustering method considering both box fractal dimension and orientation of joints |
| title_short | A new multiple-factor clustering method considering both box fractal dimension and orientation of joints |
| title_sort | new multiple factor clustering method considering both box fractal dimension and orientation of joints |
| topic | Joint clustering Box fractal dimension (BFD) Orientation Hard boundary |
| url | http://www.sciencedirect.com/science/article/pii/S1674775521001372 |
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