基于Python语言的可视化空间数据库智能查询系统  

Intelligent Query System of Visual Spatial Database Based on Python Language

作　　者：董玉霞 苏荣聪 DONG Yuxia;SU Rongcong(School of Software, Quanzhou University of Information Engineering,Quanzhou, Fujian 352000,China)

机构地区：[1]泉州信息工程学院软件学院,福建泉州352000

出　　处：《平顶山学院学报》2022年第2期50-54,共5页Journal of Pingdingshan University

基　　金：福建省本科教育教学改革重大项目(FBJG20190137)。

摘　　要：针对传统的可视化空间数据库智能查询系统存在查询错误率高的问题,设计基于Python语言的可视化空间数据库智能查询系统.获取异构存储分布,通过融合度聚类分析,进行可视化空间数据库的异构样本特征分解,根据分解结果,采用模糊度检测和K均值聚类方法,对可视化空间数据库的差异性数据聚类,以聚类结果为基础,结合随机自适应调度和子空间压缩方法,实现对可视化空间数据库的智能查询.仿真实验结果表明,采用该方法进行可视化空间数据库智能查询的错误率较低,查准率较高,数据特征聚类性较强.Aiming at the problem of high query error rate in the traditional visual spatial database intelligent query system,a visual spatial database intelligent query system based on Python language is designed.The heterogeneous storage distribution is first obtained,the heterogeneous sample characteristics of the visual spatial database through the fusion degree clustering analysis is then decomposed and finally the differential data of the visual spatial database is clustered by using the ambiguity detection and K-means clustering methods according to the decomposition results.Based on the clustering results,the intelligent query of visual spatial database is realized with the random adaptive scheduling and subspace compression methods.The simulation results show that this method has low error rate,high precision and strong clustering of data features.

关 键 词：PYTHON语言 可视化 空间数据库 智能查询 K均值聚类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]