Adaptive Spatial Clustering for Multi-Dimensional Data and Its Cloud Model Representation

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.