摘要
为了提高居民地面实体匹配的准确度,提出一种基于概率松弛模型的不同比例尺面状居民地匹配算法。首先,依据道路信息划分面状居民地数据,每次运行算法只处理一个道路网眼内的面状居民地;然后,扩展初始匹配模式,正反向计算居民地面实体之间和居民地面实体匹配到空两种匹配概率,并根据邻近匹配对的兼容性不断更新初始概率矩阵,直至相邻两次迭代矩阵内匹配概率变化量均小于某一阈值;最后,根据设定的选取规则选出1∶0、1∶1、1∶M和M∶N等4种匹配对。实验结果表明,本文所提方法可以有效准确地识别出4种匹配关系,明显减少了误匹配和漏匹配。
In order to improve the matching accuracy,this pa per proposes a matching algorithm for areal settlements at different scales based on probabilistic relaxation model.The proposed method first partitions two areal settlements datasets into subsets using road information,so that at each run the algorithm deals only with the areal settlements in one road mesh.After that,the initial matching mode is extended to calculate bidirectional matching probability between areal settlements and between areal settlement to null.And then,continuously updates the initial probability matrix according to the compatibility of adjacent matching pairs until the matching probability variations in matrix of two consecutive iterations are less than a certain threshold.Finally,four matching pairs of 1:0,1:1,1:M and M:N are selected according to the selection rule we set.The results indicate that the algorithm proposed in this paper can effectively and accurately identify four matching relationships and significantly reduce the number of mismatched pairs and missed matched pairs.
作者
刘洁
郭庆胜
王勇
陈恒
LIU Jie;GUO Qingsheng;WANG Yong;CHEN Heng(School of Resources and Environment Science,Wuhan University,Wuhan 430079,China;Chinese Academy of Surveying and Mapping,Beijing 100830,China)
出处
《测绘地理信息》
CSCD
2023年第2期138-142,共5页
Journal of Geomatics
基金
国家自然科学基金(41871378)。
关键词
面状居民地
实体匹配
道路网眼
概率松弛
areal settlement
entity matching
road mesh
probabilistic relaxation
