基于PSO-Elman高速公路交通流预测研究

Research on the prediction of traffic flow based on PSO-Elman neural network

本文提出了基于粒子群算法(PSO)的Elman神经网络混合优化策略,采用PSO优化连接权值来训练神经网络,与标准BP算法相比,PSO采用实数编码,结构简单,学习收敛快,仿真结果表明该模型适合于高速公路短期交通流预测.

A PSO algorithm is used to train the Elman neural network.Compared with the standard BP algorithm,PSO,which uses real coding,has more simple structure and faster convergence study.The simulation results show that the model is suitable for highway traffic flow short-termforecasting.