摘要
由于现行海量不完整数据近似查询系统存在概率查询能力较差、查询时间过长、查询误差过大等问题,基于改进K近邻算法设计了一种新的海量不完整数据近似查询系统,并对系统的硬件和软件进行设计。通过信息源端、切换整合平台、查询端构建整体架构,选用4路模拟量差分输入、8632C004的P1同两片TKB730的输入/输出连接、SJW000电路、82B250电路、CAN总线连接电路构成系统硬件结构。由数据采集、数据查询、数据判断实现软件查询,同时设定嵌入式仿真软件、用户审计控制软件完成信息查询。实验结果表明,基于改进K近邻算法的海量不完整数据近似查询系统能够有效提高概率查询能力,缩短查询时间,降低查询误差。
Since the probabilistic query ability of the existing approximate query system for massive incomplete data is poor,its query time is too long,and its query error is too large,a new massive incomplete data approximate query system based on the improved K⁃nearest neighbor(KNN)algorithm is designed.The hardware and software of the system are designed.The overall architecture is constructed by the information source terminal,the switching integration platform and the query terminal.The hardware structure of the system is constructed by 4⁃way analog differential inputs,connections between P1 of 8632C004 and the input/output of two pieces of TKB730,SJW000 circuit,82B250 circuit and CAN bus connecting circuit.The software query is realized by data collection,data query and data judgment.The embedded simulation software and user audit control software are set to complete information query.The experimental results show that the massive incomplete data approximate query system based on the improved KNN algorithm can effectively improve the probabilistic query ability,shorten the query time and reduce the query error.
作者
徐宝磊
XU Baolei(Sichuan University of Arts and Science,Dazhou 635000,China)
出处
《现代电子技术》
2021年第15期177-181,共5页
Modern Electronics Technique
关键词
近似查询系统
海量不完整数据
改进K近邻算法
数据采集
数据查询
不完整分析
近似分析
approximate query system
massive incomplete data
improved KNN algorithm
data collection
data query
incompleteness analysis
approximation analysis
