工业工程2012，Vol.15Issue(4)：1-6,6.DOI:10.3969/j.issn.1007-7375.2012.04.001
基于组合预测模型的铁路集装箱运量预测
Forecast of Railway Container Freight Volume by Using a Combinatorial Model
摘要
Abstract
The forecast of railway container freight volume has significant effect on the operation and development of the railway. The existing forecast models can forecast a single index only, which is not accurate enough. To overcome this disadvantage, the combinatorial forecast model is adopted to forecast railway container freight volume. Based on the historical data, individual index forecast models are derived by u-sing linear polynomial and grey models, respectively. Then, the individual index forecast models are combined by using radial basis function (RBF) neural network. Analysis shows that, in comparison with two single index forecast models, the combinatorial forecast model can improve the forecast result of relative error by 3. 19% and 12.76% , respectively. Finally, the combinatorial forecast result is analyzed and modified by Markov chain model.关键词
铁路集装箱/预测/径向基神经网络/马尔科夫链Key words
railway container/ forecast/ radial basis function (RBF) neural network/ Markov chain分类
交通工程引用本文复制引用
林炳焜,程文明,于兰峰..基于组合预测模型的铁路集装箱运量预测[J].工业工程,2012,15(4):1-6,6.基金项目
国家自然科学基金资助项目(51175442) （51175442）
中央高校基本科研业务费专项资金专题研究资助项目(2010ZT03) （2010ZT03）
高等学校博士学科点资助项目(200806131014) （200806131014）
