【摘要】 为了提高空间数据的利用效率,需要对多空间数据库内存数据位置匹配方法进行研究。采用当前方法对多空间数据库中的空间数据位置进行匹配时,得到的匹配结果与实际结果之间的误差较大,匹配所用的时间较长,存在匹配结果准确率低和匹配效率低的问题。提出一种多空间数据库内存数据位置实时匹配方法,在四叉树分解规则的基础上将多空间数据库内存数据分为大小相同的若干个网格,采用空间填充曲线表示方法对网格进行编码,得到数据量相同的多个区间,完成多空间数据库内存数据的均衡划分。分析多空间数据库内存数据的趋向性,建立趋势函数,得到空间数据属性差异和空间距离的相似度,在趋势函数的基础上根据相似度建立多空间数据库内存数据位置匹配模型,完成多空间数据库内存数据位置的实时匹配。实验结果表明,所提方法的匹配结果准确率高、匹配效率高。更多还原

【Abstract】 In order to improve the utilization efficiency of spatial data,it is necessary to study the method of position matching for multi-space database memory data. For the current method,the error between the matching result and the actual result is too large. Meanwhile,the matching time is long,leading to low accuracy of matching result and low matching efficiency. In this article,a real-time matching method for position of memory data in multi-space database was proposed. Based on the quaternary tree decomposition rule,the multi-space database memory data was divided into several grids with the same size. Then,the space-filling curve method was used to encode the grid,so as to obtain some intervals with the same amount of data. The equilibrium division of memory data in multi-space database was completed. Moreover,the tendency of multi-space database memory data was analyzed and the trend function was established to get the similarity degree between spatial data attribute difference and spatial distance. Finally,the model of position matching for multi-space database memory data based on similarity and trend function. Thus,the real-time matching of position for multi-space database memory data was completed. Simulation results prove that the proposed method has high matching accuracy and efficiency.更多还原