Adaptive Spatial Clustering for Multi-Dimensional Data and Its Cloud Model Representation
Authors: 
Bin Gao, Xinhai Zhang, Xiaobin Xu, Yifeng LiuAuthors Info & Claims
Bin Gao, Xinhai Zhang, Xiaobin Xu, Yifeng LiuAuthors Info & ClaimsPages 69 - 73
Abstract
In view of the problem that the number of clusters need to be set manually, it is difficult to process the multi-dimensional data effectively, and the clustering results are not described effectively when the multi-dimensional data need to be clustered. This paper proposes a method of adaptive spatial clustering and its cloud model representation for the multi-dimensional data. This method can be used to cluster multi-dimensional spatial data, form qualitative description of clustering results, and realize the reconstruction and verification of qualitative description features. Through simulation experiments, this method can cluster data adaptively without the need to set the number of clusters. At the same time, it has a good ability to abstract and reconstruct digital features.
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- Adaptive Spatial Clustering for Multi-Dimensional Data and Its Cloud Model Representation
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Published In
April 2020
563 pages
ISBN:9781450377089
DOI:10.1145/3404555
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- University of Tsukuba: University of Tsukuba
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 August 2020
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- Research-article
- Research
- Refereed limited
Funding Sources
- the Open Research Fund of Key Laboratory of Space Utilization
- This research is supported in part by National Key Research and Development Project
- the International Research Cooperation Seed Fund of Beijing University of Technology
Conference
ICCAI '20
ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence
April 23 - 26, 2020
Tianjin, China
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