The Mining Method of the Road Traffic Illegal Data Based on Rough Sets and Association Rules

摘要：

Based on the daily operation data of the urban road traffic management system, this paper analysis the demand of data mining of the traffic violations, pre-processes the data to data sets by the detection methods of proximity-based outlier. According to the characteristics of data traffic offense, combining the advantages of rough sets and association rules data mining, proposed two methods based on the joint data mining method. Finally, a city in the year 2008 road traffic management data, for example, using the text method, regularity of the traffic offense causes were analyzed, indicating that the method is effective.

关键词： Traffic violate Rrough sets Association rules Anomaly detection theory Data mining

作者: Wei Cheng Xiaofeng Ji Chunhua Han Jianfeng Xi

作者单位: ITS Center Kunming University of Science and Technology Kunming, China College of Transportation Jilin University Changchun, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 3218-3221

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）