模糊聚类分析在CPⅠ复测控制点稳定性分析中的应用  

Study on Application of Fuzzy Clustering Analysis in StabilityAnalysis of CPⅠ Repetition Survey Control Points

作　　者：贾华垒 岳东杰[1] Jia Hualei;Yue Dongjie(College of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China)

机构地区：[1]河海大学地球科学与工程学院,江苏南京211100

出　　处：《甘肃科学学报》2021年第1期31-35,共5页Journal of Gansu Sciences

摘　　要：高铁CPⅠ控制网点是高铁测量首级控制网,点位置精度和稳定性分析都对高铁建设质量至关重要,而稳定性本身是一个模糊概念,在稳定与不稳定之间不存在严格的界限。针对稳定性没有明确有效的判断界限,为了更准确地判断出控制点的稳定性情况,结合某高铁CPⅠ控制网17个控制点的两期观测数据,采用模糊聚类原理进行分析,找出了2个最不稳定点和15个相对稳定点的集合,验证了该理论在CPⅠ控制点稳定性分析中的适用性。The high-speed rail CPⅠcontrol network is the first-level control network for high-speed rail measurement.The point position accuracy and stability analysis are both crucial to the quality of high-speed rail construction.Stability itself is a vague concept,and there is no strict boundary between stability and instability.In view of the fact that there is no clear and effective judgment limit for stability.In order to more accurately determine the stability of the control point,the fuzzy clustering principle is used for analysis,combined with the observation data of 17 control points of a high-speed rail CPⅠcontrol network.With two sets of the most unstable points and 15 relatively stable points,the fuzzy clustering principle is used to analyze the applicability of the theory in the stability analysis of CPⅠcontrol points.

关 键 词：CPⅠ 稳定性 模糊相似矩阵 聚类分析 

分 类 号：P258[天文地球—测绘科学与技术]