The invention relates to the technical field of traffic, in particular to a traffic flow prediction method based on a particle swarm optimization neural network. The method comprises the following steps: S1, obtaining and preprocessing a traffic flow data sample, wherein the traffic flow data sample comprises a test sample and a training sample; S2, setting parameters of a BP neural network model,and constructing the BP neural network model for traffic flow prediction; S3, optimizing a connection weight value and a threshold value of the BP neural network model by adopting a particle swarm algorithm to enable a global error of the BP neural network model to reach preset precision; S4, importing the training sample into the BP neural network model optimized by the particle swarm algorithmfor training, and performing actual prediction after the training is completed; and S5, realizing prediction of a short-time traffic condition through simulation, and evaluating the state of the traffic flow. According to the method, the problems that when a traditional BP neural network is used for traffic flow prediction, convergence is slow, the BP neural network is prone to falling into a local optimal value, and an oscillation effect is caused are solved.

    本发明涉及交通技术领域,特别涉及一种基于粒子群优化神经网络的交通流预测方法,包括如下步骤:S1、获取交通流数据样本并进行预处理;所述交通流数据样本包括测试样本与训练样本;S2、设定BP神经网络模型的参数,构建用于交通流预测的BP神经网络模型;S3、采用粒子群算法优化BP神经网络模型的连接权值和阈值,使所述BP神经网络模型的全局误差达到预设精度;S4、将训练样本导入到经过粒子群算法优化后的BP神经网络模型中进行训练,训练完成后在进行实际预测;S5、通过仿真实现短时交通情况的预测,以及对交通流的状态进行评估。本发明解决了传统BP神经网络在进行交通流预测时,收敛慢、容易陷入局部最优值,以及引起震荡效应的问题。


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    Title :

    Traffic flow prediction method based on particle swarm optimization neural network


    Additional title:

    一种基于粒子群优化神经网络的交通流预测方法


    Contributors:
    PENG XUSHAN (author) / SHAO YU (author)

    Publication date :

    2020-04-28


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES






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