基于组合模型的公路客运量预测研究

Research on Highway Passenger Volume Forecast Based on Combined Model

随着客运量与经济发展的联系越来越密切,如何更科学有效地对客运量进行预测变得越来越重要。文章分别介绍了灰色系统法、时间序列法、Elman神经网络及组合预测的方法原理,并以兰州市公路客运量为例,运用灰色模型、时间序列模型和Elman神经网络模型的组合模型进行客流预测,验证了该组合模型的合理性。

With the closer connection between passenger volume and economic development, how to more scientifically and effectively forecast the passenger volume is becoming increasingly important. This article introduced the method and principle of respectively gray system method,time-series method, Elrnan neural network and portfolio forecasting, and with Lanzhou highway passenger volume as the example,it used the combined model of gray model, time-series model and Elrnan neural network model for passenger volume forecast,and verified the reasonableness of this combined model.