基于改进灰色GM(1.1)模型的铁路货运量预测  

Forecast of Railway Freight Volume Based on Improved Gray GM(1.1)Model

作　　者：肖金山 何涛[1] XIAO Jin-shan;HE Tao(Research Institute,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学研究院,兰州730070

出　　处：《兰州交通大学学报》2021年第3期40-45,共6页Journal of Lanzhou Jiaotong University

摘　　要：针对铁路货运量年度长期预测对货运部门制定短期运输规划指导不足的问题,引入GM(1.1)模型预测铁路月度货运量.考虑货运量序列常呈振荡波动的特征,利用加速平移变换和加权均值变换弱化序列的波动性后,建立改进灰色GM(1.1)模型实现最终预测.对我国2019年11月至2020年5月铁路月度货运量序列拟合结果比较表明,与传统GM(1.1)模型相比,改进GM(1.1)模型在预测精度方面明显提高,能更好的拟合铁路月度实际货运量,解决了传统GM(1.1)模型对呈现振荡波动现象的铁路货运量预测精度较低的问题.The GM(1.1)model is introduced to predict the monthly freight volume of the railway in order to solve the problem that the annual long-term forecast of railway freight volume is insufficient to guide the freight department to formulate shot-term transport planning.Considering that the freight volume sequence is usually characterized by oscillating fluctuation,an improved grey GM(1.1)model is established to realize the final prediction after the accelerated translation transformation and weighted mean transformation are used to weaken the fluctuation of the sequence.Through the simulation of China's railway monthly freight volume from November 2019 to May 2020,it is found that the improved GM(1.1)model has significantly improved the prediction accuracy compared with the traditional GM(1.1)model.This method better fits the actual railway monthly freight volume,and solves the problem that the traditional GM(1.1)model has low accuracy in predicting the railway freight volume with oscillating fluctuations.Compared with the traditional GM(1.1)model,the prediction accuracy of the improved GM(1.1)model is significantly improved,and the improved GM(1.1)model can better fit the monthly actual railway freight volume,which solves the problem that the traditional GM(1.1)model has a low accuracy in predicting the railway freight volume with oscillating fluctuations.

关 键 词：铁路月度货运量 运输规划 改进GM(1.1)模型 预测 

分 类 号：U294.1[交通运输工程—交通运输规划与管理]