摘要
通过对影响交通流原因进行分析,创建交通流预测模型,并且对模型进行仿真实验.结果表明,BP神经网络模型与径向基网络模型仿真实验效果明显,证明了预测模型的有用性.对比两种模型,BP神经网络模型效率与精准率更高.
After the analysis of the causes affecting the traffic,a traffic flow prediction model is created,and the simulation experiments are conducted on the model.The results show that the simulation experiments with BP neural network mode and radial basis network mode have both produced good results,proving the usefulness of the model in prediction.Compared with the radial basis network mode,the model under BP neural network mode can predict more efficiently and accurately.
作者
于龙
YU Long(Anshan Provincial Public Security Bureau,Anshan 114000,China)
出处
《玉溪师范学院学报》
2022年第3期68-72,共5页
Journal of Yuxi Normal University
基金
2018-2020年度沈阳市社会科学优秀学术成果二等奖“新时代城市轨道交通公共安全风险一体化防控研究”(编号:SYSKJ-2020-057)的延展性成果.
关键词
神经网络
城市交通
交通流量预测模型
neural network
urban traffic
traffic flow
forecasting model
