交通运输工程与信息学报

结合灰色模型在短期预测中的优势和马尔柯夫链在长期预测和对随机波动性数据处理方面具有的优势,根据将一个新息数据充实到原始数据序列中进行预测时是否去除其左边的第一个老数据,分别定义并建立了定维和变维动态灰色马尔柯夫预测模型;通过对我国铁路客货运量进行预测,表明动态灰色马尔柯夫预测模型优于静态灰色马尔柯夫模型和灰色模型,并且定维动态型预测效果优于变维动态型。

By comprehensive analyzing the advantages of the grey model when it is used in a short period prediction and the Markov process when it is used in a long period prediction and to deal with the stochastic fluctuation data according to whether or not removing the first older data on the left of the original data when appending a new prediction data to make prediction,a fixed and changeable dimensional dynamic grey-markov prediction model was defined and established respectively.Throuth predicting the railway passenger and freight volumes of China,it demonstrates that the dynamic grey-Markov prediction model is better than the static one and the grey model,and the prediction result of the fixed dimensional type is better than the changeable dimensional one.