一种地理空间网络子集快速探测方法  

A Fast Detection Method for Geospatial Network Subset

作　　者：吴智慧 WU Zhihui(Guangzhou Urban Planning Survey,Design and Research Institute,Guangzhou 510060,China)

机构地区：[1]广州市城市规划勘测设计研究院,广东广州510060

出　　处：《现代信息科技》2024年第15期65-68,共4页Modern Information Technology

摘　　要：针对大数据下地理空间网络子集探测效率较低的问题,文章通过引入“弧段到点”和“点到弧段”两个索引表,提出了一种地理空间网络子集快速探测方法。该方法创新性地通过两个索引表直接实现了弧段和端点的查找定位,避免了传统子集探测方法中因查找搜索计算冗余度过高导致的效率低下问题,显著提升了地理空间网络子集探测的计算效率。通过MATLAB软件模拟生成了包含不同数量随机点的狄洛尼三角网,利用该方法和传统方法分别进行了子集探测。结果表明,两种方法均可实现子集的成功探测,但是该方法显著改善了子集探测效率。Aiming at the problem of low detection efficiency of geospatial network subsets under big data,this paper proposes a fast detection method for geospatial network subsets by introducing two index tables of“arc to point”and“point to arc”.This method innovatively realizes the search and positioning of arcs and points directly through the two index tables,avoids the inefficiency caused by excessive search calculation redundancy in traditional subset detection methods,and significantly improves the calculated efficiency of geospatial network subset detection.The Delaunay Triangulation network containing different numbers of random points is simulated and generated by MATLAB software,and the subset detection is carried out by using the proposed method in this paper and the traditional method.The results show that both methods can achieve successful subset detection,but the method proposed in this paper significantly improves the efficiency of subset detection.

关 键 词：地理空间网络 子集探测 索引表 

分 类 号：TP39[自动化与计算机技术—计算机应用技术] TP208[自动化与计算机技术—计算机科学与技术]