基于灰色线性回归模型的哈尔滨铁路枢纽客运量预测研究

Study on Passenger Traffic Prediction at Harbin Railway Hub Using Grey Linear-regression Model

客运量是铁路客运枢纽规划的基础,准确掌握铁路客运量的发展规律,可为铁路枢纽制定运输计划与线路改造等提供参考依据。由于铁路客运系统是一个信息不完全的灰色系统,在进行客运量预测时,将灰色预测模型与线性回归模型结合,消除单一模型在预测过程中产生的较大误差,使模型更加灵活、预测数据更加准确。采用该模型预测哈尔滨铁路枢纽客运量,对模型精度进行评价检验,验证结果表明:评价指标方差比与小误差概率均为第一等级,评价检验结果为优,预测结果可靠。

Given that passenger traffic serves as the basis for the planning of railway passenger hub, a precise grasp on its development may provide references to the development of transport plan and to the upgrade of railway lines at the hub. As the railway passenger transport system constitutes a grey system with only limited information, the paper integrates the grey prediction model and the linear regression model in the prediction of passenger volume to avoid the large error that may occur in the application of just one single prediction model. As a result, the method provides better flexibility and precision in its prediction. The paper applies this approach to the traftic prediction at Harbin railway hub to evaluate and verify the model. The results indicate that the variance ratio of the evaluation index and the probability of small error are both categorized to class one, which means that the approach can be considered as a valid one and the prediction results are reliable.