文章基本信息

标题：Geometrical Approach to a New Hybrid Grid-Based Gravitational Clustering Algorithm
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作者：Faisal Bin Al Abid ; A.N.M. Rezaul Karim ; Golam Rahman Chowdhury 等
期刊名称：Journal of Computer Science
印刷版ISSN：1549-3636
出版年度：2021
卷号：17
期号：3
页码：197-204
DOI：10.3844/jcssp.2021.197.204
出版社：Science Publications
摘要：In the past years, several clustering algorithms have been developed, for example, K-means, K-medoid. Most of these algorithms have the common problem of selecting the appropriate number of clusters and these algorithms are sensitive to noisy data and would cause less accurate clustering of the data set. Therefore, this paper introduces a new Hybrid Grid-based Gravitational Clustering Algorithm (HGGCA) geometrically, which can automatically detect the number of clusters of the targeted data set and find the clusters with any arbitrary forms and filter the noisy data. This proposed clustering algorithm is used to move the cluster centers to the areas where the data density is high based on Newton’s law of gravity and Newton’s laws of motion. Also, the proposed method has higher accuracy than the existing K-means and K-medoids methods which is shown in the experimental result. In this study, we used cluster-validity-indicators to verify the validity of the proposed and existing methods of clustering. Experimental results show that the proposed algorithm massively creates high-quality clusters.
关键词：Clustering;Newton’s Law of Gravity;Euclidean Distance;Newton’s Law of Motion;Cluster Validity Index