铁道标准设计2016，Vol.60Issue(10)：27-30,4.DOI:10.13238/j.issn.1004-2954.2016.10.007
基于马尔科夫-Verhulst模型的铁路货运量预测研究
Research on Railway Freight Volume Prediction Based on Markov Verhulst Model
摘要
Abstract
Railway freight volume is one of the leading indicators of economic development in an area and accurate prediction of railway freight volume may serve as guidance to the development planning of this area. This paper is focused on the model error of the traditional grey Verhulst model used in railway freight volume forecasting to improve its prediction accuracy. Markov Chain model is used to modify and improve traditional Verhulst model. In the end, practical cases are introduced to verify the significance of Markov Chain to improve the prediction accuracy of the gray verhulst model, which is proved suitable for Gansu railway freight volume forecast. Therefore, the application of this model to predict the railway freight volume in Gansu province from 2015 to 2017 provides reliable indicators for the development of logistics, transportation and other related industries in the region.关键词
物流运输/铁路货运量/Verhulst模型/马尔科夫链模型/预测Key words
Logistics and transportation/Railway freight volume/Verhulst model/Markov chain model/Prediction分类
交通工程引用本文复制引用
袁胜强,鲍学英,王起才..基于马尔科夫-Verhulst模型的铁路货运量预测研究[J].铁道标准设计,2016,60(10):27-30,4.基金项目
长江学者和创新团队发展计划滚动支持(IRT15R29) （IRT15R29）
