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面向大规模交互数据空间划分的Voronoi图生成算法及应用
引用本文:熊鹏文,周晓芸,熊宏锦,张婷婷. 面向大规模交互数据空间划分的Voronoi图生成算法及应用[J]. 国防科技大学学报, 2022, 44(1): 129-136. DOI: 10.11887/j.cn.202201019
作者姓名:熊鹏文  周晓芸  熊宏锦  张婷婷
作者单位:南昌大学 信息工程学院, 江西 南昌 330031;海装驻武汉地区军事代表局, 湖北 武汉 333000;陆军工程大学 指挥控制工程学院, 江苏 南京 210007
基金项目:国家自然科学基金资助项目(62163024,61903175,61663027);江西省主要学科学术和技术带头人项目(20204BCJ23006)
摘    要:传统Voronoi图对大量点集进行Voronoi划分时会产生Voronoi单元格数过多的现象,导致难以适用于地理信息系统、生物医学等诸多领域.为了解决这个问题,提出一种自适应基于密度的聚类算法(Density-Based Spatial Clustering of Applications with Noise,DBS...

关 键 词:Voronoi图  聚类  自适应参数  空间划分
收稿时间:2020-08-07

Voronoi diagram generation algorithm and application for large-scale interactive data space partition
XIONG Pengwen,ZHOU Xiaoyun,XIONG Hongjin,ZHANG Tingting. Voronoi diagram generation algorithm and application for large-scale interactive data space partition[J]. Journal of National University of Defense Technology, 2022, 44(1): 129-136. DOI: 10.11887/j.cn.202201019
Authors:XIONG Pengwen  ZHOU Xiaoyun  XIONG Hongjin  ZHANG Tingting
Affiliation:School of Information Engineering, Nanchang University, Nanchang 330031, China;Wuhan Military Representatives Bureau of Naval Equipment Department, Wuhan 333000, China; Command and Control Engineering College, Army Engineering University, Nanjing 210007, China
Abstract:When the traditional Voronoi diagram divides a large number of point sets into Voronoi, there are too many Voronoi cells, which makes it difficult to apply to such fields as geographic information systems and biomedicine. In order to solve this problem, a Voronoi diagram based on adaptive DBSCAN (density-based spatial clustering of applications with noise) was proposed. The phenomenon of Voronoi unit merge was explained. The necessary and sufficient conditions for its occurrence were proved. The algorithm for generating the Voronoi diagram was proposed and simulated. In order to verify its effectiveness, the algorithm was applied to neutrophils under the microscope and fire point data on the surface of China. The results show that the algorithm can effectively solve the problem that Voronoi diagram is too meticulous when the point set size is large, which breaks through the single point to single point division form of the traditional Voronoi diagram. In addition,the algorithm broadens the application of Voronoi diagrams in the fields of graphic image processing,biomedicine and geographic information systems.
Keywords:Voronoi diagram   clustering   adaptive parameters   space division
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