Short-term Traffic Flow Prediction for Road Tunnel Using Fuzzy Data Mining

摘要：

It is very difficult to predict short-term traffic flows of road tunnel because they have high complexity, fuzziness and randomicity. The fuzzy data mining method is adopted to process the past traffic flow data at the same period of time to obtain their clustering modes. Based on these, the predicted data sample is inferred to be close to or belong to which modes. The new traffic flow is predicted with the past data of the same mode whose data samples have high similarity. The analysis and computing results show the method is easy to be implemented,and has higher prediction precision than the other methods without clustering analysis to the raw data.

关键词： Information processing Road tunne Traffic flow Prediction Fuzzy data mining

作者: LAN Hongli LUO Wenguang

作者单位: Department of Computer Engineering Guangxi University of Technology Liuzhou, Guangxi Province, China Department of Electronic Information and Control Engineering Guangxi University of Technology Liuzho

会议类型: 国际会议

会议名称: 第一届国际计算机新科技与教育学术会议(Proceedings of the First International Conference on Computer Science & Education ICCSE2006)

会议地点: 厦门

会议语种:英文

页码: 301-304

在线出版日期: 2006-07-27（万方平台首次上网日期，不代表论文的发表时间）