摘要
针对DBSCAN算法时间开销大的缺点,提出了基于网格单元的DBSCAN算法,通过对数据空间进行网格单元划分来优化DBSCAN算法中最耗时的区域查询过程,省去了大量不必要的查询操作,并分析了网格单元的划分方式对本文算法的影响,通过选取最优划分方式,提高整个算法的运行效率。通过仿真实验,验证了基于网格单元的DBSCAN算法具有较高的准确率和较低的时间复杂度。
To overcome the time overhead shortcoming of Density Based Spatial Clustering of Applications with Noise （DBSCAN） algorithm, a modified DBSCAN algorithm based on grid cell is proposed. Using this algorithm the data space is divided into grid cells and large number of unnecessary operations is eliminated, thus the region query process, which is the most timeconsuming in DBSCAN algorithm, is optimized. The effects of different grid division methods are analyzed to select the optimal division method, thus improving the total operation efficiency of the algorithm. Simulation results verify that the modified DBSCAN algorithm based on grid cell has higher accuracy and lower time complexity.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2014年第4期1135-1139,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(60973041)
'863'国家高技术研究发展计划项目(2009AA010314)
中央高校基本科研业务费专项资金资助
吉林省科技发展计划项目(2011507)
关键词
计算机应用
数据挖掘
聚类分析
DBSCAN
网格单元
computer application
data mining
cluster analysis
density-based spatial clustering of applications with noise（DBSCAN）
grid cell
