A mean shift algorithm incorporating reachable distance for spatial clustering
Spatial clustering is a widely used technique in spatial analysis that groups similar objects together based on their proximity in space. However, traditional clustering algorithms often fail to ensure the accessibility of cluster centers, which limits their validity in practical applications such a...
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| Veröffentlicht in: | Information sciences Jg. 689; S. 121456 |
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| Sprache: | Englisch |
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01.01.2025
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| ISSN: | 0020-0255 |
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| Abstract | Spatial clustering is a widely used technique in spatial analysis that groups similar objects together based on their proximity in space. However, traditional clustering algorithms often fail to ensure the accessibility of cluster centers, which limits their validity in practical applications such as facility location problems. To address this issue, this article introduces a novel Mean Shift algorithm that incorporates reachable distance and an iterative mechanism to accurately locate cluster centers. The proposed algorithm initially labels clustering elements with road network coordinates to facilitate the calculation of reachable distance and the cluster center iterative mechanism. Subsequently, the mean shift vector function is modified to employ reachable distance as the measure of geographic reachable similarity. Unlike existing algorithms, our approach allows for cluster centers to be positioned independently of the clustering elements, guaranteeing geographical accessibility. Through simulation experiments, we demonstrate that our proposed algorithm not only outperforms existing methods in terms of solution quality, but also effectively addresses the limitations of disregarding geographical obstacles and unreachable cluster centers. |
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| AbstractList | Spatial clustering is a widely used technique in spatial analysis that groups similar objects together based on their proximity in space. However, traditional clustering algorithms often fail to ensure the accessibility of cluster centers, which limits their validity in practical applications such as facility location problems. To address this issue, this article introduces a novel Mean Shift algorithm that incorporates reachable distance and an iterative mechanism to accurately locate cluster centers. The proposed algorithm initially labels clustering elements with road network coordinates to facilitate the calculation of reachable distance and the cluster center iterative mechanism. Subsequently, the mean shift vector function is modified to employ reachable distance as the measure of geographic reachable similarity. Unlike existing algorithms, our approach allows for cluster centers to be positioned independently of the clustering elements, guaranteeing geographical accessibility. Through simulation experiments, we demonstrate that our proposed algorithm not only outperforms existing methods in terms of solution quality, but also effectively addresses the limitations of disregarding geographical obstacles and unreachable cluster centers. |
| ArticleNumber | 121456 |
| Author | Luo, Yalan Xie, Chengwang Zhang, Qiongbing Peng, Youwei |
| Author_xml | – sequence: 1 givenname: Youwei surname: Peng fullname: Peng, Youwei email: ywpHnust@mail.hnust.edu.cn organization: Hunan University of Science and Technology, Taoyuan Road, Yuhu District, Xiangtan, 411201, HuNan, China – sequence: 2 givenname: Yalan surname: Luo fullname: Luo, Yalan email: lyl1@mail.hnust.edu.cn organization: Hunan University of Science and Technology, Taoyuan Road, Yuhu District, Xiangtan, 411201, HuNan, China – sequence: 3 givenname: Qiongbing orcidid: 0000-0002-8452-0745 surname: Zhang fullname: Zhang, Qiongbing email: mrtly2@whu.edu.cn organization: Hunan University of Science and Technology, Taoyuan Road, Yuhu District, Xiangtan, 411201, HuNan, China – sequence: 4 givenname: Chengwang surname: Xie fullname: Xie, Chengwang email: chengwangxie@m.scnu.edu.cn organization: South China Normal University, Ma'gong Street, Shanwei, 516600, Guangdong, China |
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| Keywords | Spatial clustering Cluster center iteration mechanism Mean shift algorithm Geographical accessibility |
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| Title | A mean shift algorithm incorporating reachable distance for spatial clustering |
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