为了提高全国铁路客流预测精度，针对铁路客流变化的影响因素及特点，对GM（1，1）模型进行改进，提出了多次修正残差灰色模型的铁路客流预测方法。克服了传统的GM（1，1）模型的指数函数预测精度较差、单次修正残差精度不够的缺点，通过多次残差修正，减少预测误差。结合2003-2010年铁路客运数据实例分析。结果证明该方法预测误差小、精度高、计算简便、可操作性强，为铁路客流预测提供了一种更为可行的途径。%In order to increase the forecast accuracy of the national railway passenger flow,this study improves GM(1,1)model and proposes the railway passenger flow prediction method based on residual error gray mod-el in light of factors and characteristics of railway passenger flow. By conquering some weaknesses,such as the inaccurate prediction of the exponential function in traditional GM(1,1)model and the inaccurate single resid-ual correction,the forecast error is reduced with many times of residual modification. Based on the analysis of railway passenger flow data during 2003-2010,the prediction method based on residual error gray model has such advantages as small error,high precision,easy calculation and operability,which provides a feasible ap-proach for the railway passenger flow forecast.
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