Short-term Traffic Flow Prediction Based on BP Artificial Neural Networks

摘要：

The coordination of control system and guidance system can solve currently urban congestion effectively, and traffic flow prediction is an important part for achieving this process. This paper establishes a short-term traffic flow predicting model of single intersection, then proves the feasibility of BP neural network being used in traffic flow prediction with several kinds of algorithms. Finally the results show that the method has very good applicability in practical engineering project.

关键词： congestion coordination traffic flow prediction BP neural network MatLab

作者: Manrong Yuan Zhaosheng Yang Juan Meng

作者单位: Traffic & Transportation College Jilin University Changchun, China College of Traffic and Transportation & State Key Lab of Automobile Dynamic Simulation Jilin Univers

会议类型: 国际会议

会议名称: 2010 International Conference on Future Information Technology(2010年未来信息技术国际会议 ICFIT 2010)

会议地点: 长沙

会议语种:英文

页码: 162-165

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）