Modified-DBSCAN Clustering for Identifying Traffic Accident Prone Locations

机译：修改后的DBSCAN群集，用于识别容易发生交通事故的位置

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

Road traffic accidents, especially expressway traffic accidents, have become a severe problem in China. Under this condition, identification of road traffic accident prone locations is in urgent need. This work proposes a modification of DBSCAN clustering algorithm with parameters s and minPts carefully chosen for identifying traffic accident prone locations. Experimental results on traffic accident datasets of three national expressways are given, demonstrating the effectiveness of the proposed algorithm.

机译：在中国，道路交通事故，特别是高速公路交通事故已经成为严重的问题。在这种情况下，迫切需要识别道路交通事故易发地点。这项工作提出了对DBSCAN聚类算法的修改，其中使用了经过仔细选择的参数s和minPts来识别容易发生交通事故的位置。给出了三个国家高速公路交通事故数据集的实验结果，证明了该算法的有效性。

著录项

来源
《International conference on intelligent data engineering and automated learning》|2016年|99-105|共7页
会议地点
作者
Chenlu Qiu; Huiying Xu; Yongqiang Bao;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类
关键词
Traffic accident prone locations; DBSCAN clustering; Kurtosis;

机译：交通事故易发地点; DBSCAN集群;峰度;

相似文献

外文文献
中文文献
专利

1. Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation [J] . Michal Bil, Richard Andrasik, Zbyngk Janoska Accident Analysis & Prevention . 2013,第juna期

机译：基于核密度估计和聚类重要性评估的交通事故危险道路位置识别
2. The Application of Binary k-Means Clustering to Identify Groups of Road Traffic Accident?s Factors in United Kingdom [J] . Nur Atiqah Binti Hamzah, Sabariah Binti Saharan, Sie Long Kek Research Journal of Applied Sciences: RJAS . 2020,第4期

机译：二元k型聚类在英国识别道路交通事故群体中的应用
3. Using Data Mining Technique to Predict Cause of Accident and Accident Prone Locations on Highways [J] . Dipo T. Akomolafe, Akinbola Olutayo American Journal of Database Theory and Application . 2012,第3期

机译：使用数据挖掘技术预测公路事故和易发事故地点的原因
4. Modified-DBSCAN Clustering for Identifying Traffic Accident Prone Locations [C] . Chenlu Qiu, Huiying Xu, Yongqiang Bao International Conference on Intelligent Data Engineering and Automated Learning . 2016

机译：修改-DBSCAN聚类，用于识别交通事故易发位置
5. Evaluation and development of methods for identifying high-risk accident locations. [D] . Cheng, Wen. 2006

机译：评估和开发识别高风险事故地点的方法。
6. Clustering Analysis of Traffic Accident Risk in Turkey [O] . Ahmet TORTUM, Ahmet ATALAY 2015

机译：土耳其交通事故风险的聚类分析
7. Identification of traffic accident risk-prone areas under low-light conditions [O] . K. Ivan, I. Haidu, J. Benedek, 2015

机译：在弱光条件下识别交通事故风险易发区域
8. Accident Prevention Based on Automatic Detection of Accident Prone Traffic Conditions: Phase 1; Final rept [R] . Hourdos, J., Garg, V., Michalopoulos, P. 2008

机译：基于事故易发交通状况自动检测的事故预防：第1阶段;最终评估

Modified-DBSCAN Clustering for Identifying Traffic Accident Prone Locations

摘要

著录项

相似文献

相关主题

期刊订阅