摘要
首先对DBSCAN(Density Based Spatial Clustering of Applications with Noise)聚类算法进行了深入研究,分析了它的特点、存在的问题及改进思想,提出了基于DBSCAN方法的交通事故多发点段的排查方法及其改进思路,并且给出了实例以说明处理过程及可行性。实验结果表明本文提出的方法可以大大提高交通事故黑点排查效率。
This paper first researches DBSCAN clustering algorithm,and analyzes characteristics and existing problems of the DBSCAN algorithm and improved idea.Evaluation method of the traffic accident black spots and an improved thought based on DBSCAN are proposed.In order to illuminate course of processing and feasibility,an example is presented.The experimental result demonstrates that this paper method can greatly enhance the working efficiency of evaluation of the traffic accident black spots.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第20期216-221,共6页
Computer Engineering and Applications
基金
福建省自然科学基金(the Natural Science Foundation of Fujian Province of China under Grant No.A0310008)
福建省高新技术研究开放计划重点项目(No.2003H 043)
关键词
聚类分析
DBSCAN
交通事故多发点(段)
数据挖掘
clustering analysis
Density Based Spatial Clustering of Applications with Noise （DBSCAN）
prone location of traffic
data mining
