交通信息与安全Issue(2)：41-44,49,5.DOI:10.3963/j.issn1674-4861.2014.02.008
城市交通枢纽短期客流量的组合预测模型
A Prediction Model of Short-term Passenger Flow for Urban Transit Hubs
刘杰 1衡玉明 1赵辉 2高学金 2王普2
作者信息
- 1. 北京公联交通枢纽建设管理有限公司 北京100161
- 2. 北京工业大学电子信息与控制工程学院 北京 100124
- 折叠
摘要
Abstract
Accurate prediction of the passenger flow plays a very important role in preparing advanced organization schemes and contingency plans for urban transit hubs .Therefore ,a combinational prediction model based on BP neural network and Least Squares Support Vector Machine (LSSVM ) is proposed in this paper .First ,a BP neural network is a-dopted to present an initial prediction based on the historical passenger volume .Then ,the LSSVM model is used to refine the "initial prediction"to reach the final predicted passenger volumes at urban transit hubs .The experiment results of this paper show that the proposed model can improve the prediction accuracy of the passenger flows at urban transit hubs by 1% ,which shows that the model in this paper can overcome the uncertainty caused by a single model .关键词
客流量/BP神经网络/最小二乘支持向量机/组合预测Key words
passenger flow/BP neutral network/LSSVM/combinational prediction分类
交通工程引用本文复制引用
刘杰,衡玉明,赵辉,高学金,王普..城市交通枢纽短期客流量的组合预测模型[J].交通信息与安全,2014,(2):41-44,49,5.
