铁路客流量预测分析与研究

Prediction Analysis and Research on Railway Passenger Traffic Volume

铁路客流量预测与分析对铁路部门采取有效的应对措施具有十分重要的意义.分别应用基本的神经网络和遗传算法优化BP神经网络对客流量进行了预测,建立铁路客流量网络预测模型.分别利用以前客流量的数据对2011年和2012年的客流量做了预测验证,并对2013年的客流量做了预测,结果表明利用遗传算法优化BP神经网络得到的预测数据和实际的基本相符,该预测算法应用到客流量的预测中效果良好,具有很好的应用和推广的前景.

It is extremely important to achieve railway passenger traffic volume prediction and analysis, which is useful for the railway department to take effective countermeasures when something happened. The neural network method and genetic algorithm are used to optimize the BP neural network for traffic prediction, and establish the passenger neural network model, then the previous traffic data are also used to verify the passenger flow forecast in 2011 and 2012, and forecast the traffic volume in 2013. The result shows that the forecast data from the improved neural network is basically matched with the actual data. ＂Fherefore,the prediction algorithm has a good prospect in application and promotion because of its good effect.