基于改進聚類的hilbertr樹空間索引算法研究

1、河南大學(xué)碩士學(xué)位論文基于改進聚類的HilbertR樹空間索引算法研究姓名：王寶祥申請學(xué)位級別：碩士專業(yè)：應(yīng)用數(shù)學(xué)指導(dǎo)教師：張連堂2011-05IIIABSTRACT With the development of information society, Geographic Information System(GIS) and spatial database are widely used in water, evironment

2、,traffic,ocean,land,regional planning and so on.As the key technology of GIS and spatial database, spatial index structure has now already become the very important research topic in the interelated fields at present. Du

3、e to the massive increase of spatial data and complexity of itself, it has become the important method to satisfy the needs of constantly increased data indexing and querying by reasonable data orgnization and constructi

4、ng the high efficient spatial index structure,which is suitable for organization. Firstly, based on the concerning theory of researches on the spatial database and spatial index technology, by the comparison and analysis

5、 among the widely used and classic algorithms in the current spatial index structure, the paper does researches on the advantages and deficiencies of those algorithms and makes discussion about direction of improvement a

6、nd designing ideas of applied algorithms in spatial index. Secondly, according to the limitations and deficiencies of performance in traditional K-means clustering algorithms applied in some fields, an improved K-means c

7、lustering algorithm which constructs the high efficient spatial index by clustering analysis, is proposed based on the traditional algorithms. The algorithm has the feature that can determine the cluster amount and cente

8、r adaptively,it adopts the maximum distance method to choose reasonable cluster centers,and relies on the valid evaluation rules to make sure the amount of more perfect clusters. This algorithm makes the K value be deter