基于神经网络的公交客流量智能预测研究

Research on Intelligent Prediction of Bus Passenger Flow Based on Neural Network

针对公交客流量的精确预测问题,提出了一种基于径向基函数(RBF)神经网络的客流量预测模型,该模型采用多源数据作为输入,融入数据预处理与参数初始估计算法,运算速度快、结构简单,易于工程实现。实验结果表明,与传统BP网络模型相比,RBF网络模型的收敛速度更快、预测精度更高。

For the problem of accurate prediction of bus passenger flow,this paper proposes a passenger flow prediction model based on radial basis function(RBF)neural network.The model uses multi-source data as input,and integrates data preprocessing and parameter initial estimation algorithm.It has the advantages of fast operation,simple structure and easy engineering implementation.The experimental results show that,compared with the traditional BP network model,RBF network model has faster convergence speed and higher prediction accuracy.