基于成分关联区域相似度的面实体模糊匹配算法

叶亚琴; 万波; 陈波

doi:10.3799/dqkx.2010.044

基于成分关联区域相似度的面实体模糊匹配算法

doi: 10.3799/dqkx.2010.044

叶亚琴^{1, 2,},
万波^{1, 2},
陈波³

1.
中国地质大学信息工程学院，湖北武汉 430074
2.
地理信息系统软件及其应用教育部工程研究中心，湖北武汉 430074
3.
武汉中地数码科技有限公司，湖北武汉 430074

基金项目:

国家重点“863”项目 2007AA12Z204

国家重点“863”项目 2007AA120503

详细信息

作者简介:
叶亚琴(1979-)，女，讲师，主要从事空间数据库增量更新研究.E-mail：yeyaqin@126.com

中图分类号: TP214
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出版历程
- 收稿日期: 2010-01-15
- 刊出日期: 2010-05-01

The Fuzzy Match Algorithm between Area Object Considering Associated Area Similarities

YE Ya-qin^{1, 2
,},
WAN Bo^{1, 2},
Chen Bo³

1.
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
2.
Engineering Research Center of GIS Software and Applications, Ministry of Education, Wuhan 430074, China
3.
Wuhan Zondycyber Co., Ltd., Wuhan 430074, China

摘要

摘要: 空间目标匹配是空间数据库增量更新的第一步，也是关键一步.研究了基于空间目标匹配的变化信息的获取算法.通过研究空间数据中存在的不确定性问题，提出将模糊理论引入到空间目标匹配算法中.重点研究如何用模糊的方法解决空间目标匹配问题，并以面实体为例说明了具体匹配过程，提出了基于成分关联区域相似度的面实体模糊匹配算法.该算法利用成分关联区域的度量因子，确定模糊拓扑关系隶属度矩阵，进而量化隶属度矩阵，最终确定模糊拓扑关系分类.算法综合利用了图幅索引、成分关联因子等进行优化，简化计算复杂度，提高了算法效率.
- 实体匹配 /
- 模糊拓扑关系 /
- 成分关联区域
Abstract: Spatial objects' matching is the first step and also the key step of incremental updating for spatial database. In this paper, a spatial objects' matching algorithm for finding the changed information is studied. On the basis of the research on the uncertainty problem existing in spatial data, this paper suggests fuzzy theory is introduced to spatial objects' matching algorithm. The paper focuses on how to solve spatial objects' matching problem by using fuzzy methods. And taking the region entities as examples for studying matching process, the author proposes the region objects' matching algorithm considering associated area similarities. This algorithm firstly uses associated area similarity's measuring genes to confirm the fuzzy topological relationship matrix, then quantifies the degree of membership matrix, and finally determines the relationship between fuzzy topological classifications. By using frame index, associated area similarity's measuring genes, the algorithm optimizes and simplifies computational complexity, and improves the algorithm efficiency as well.
- spatial objects' matching /
- fuzzy topologic relation /
- associated area

HTML全文

图 1 空间目标匹配的分类

Fig. 1. The kinds of spatial objects match

下载: 全尺寸图片幻灯片

图 2 成分关联区域(a)和其形状(b)

Fig. 2. Associated area (a) and its shape (b)

下载: 全尺寸图片幻灯片

图 3 基于CAAS-FMA分类的面实体匹配算法的步骤

Fig. 3. The steps of the match algorithm between area object considering associated area similarities

下载: 全尺寸图片幻灯片

图 4 因实体合并产生的N∶1(a)和因实体分割产生的1∶N(b)匹配结果

Fig. 4. The result of N∶1 match which caused by objects'combination (a) and 1∶N match which caused by objects'split (b)

下载: 全尺寸图片幻灯片

表 1 实体匹配检验数据说明(1996-1997)

Table 1. The introduction to the data used in the test of objects match

源类名	比较类名	实体总数	匹配耗时	差异实体个数
DLTB1996	DLTB1997	1 728	5 s	20

下载: 导出CSV

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