基于成分关联区域相似度的面实体模糊匹配算法

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. 

The Fuzzy Match Algorithm between Area Object Considering Associated Area Similarities

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.