摘要
铁路运输是一个复杂的系统 ,国民经济对其有巨大影响。本文在国民经济对铁路运输影响的定性分析基础上 ,选取了国内生产总值指数、第二产业比重、原煤产量、钢产量、港口货物吞吐量、基本建设投资、铁路市场份额、铁路货运量 8个指标作为影响因素指标 ,运用BP神经网络模型建立它们与货运量之间的联系 ,并依此对铁路的货运量进行预测 。
Railway transportation system is a complex system, and it is greatly influenced by national economy. Based on the qualitative analysis of the influence, we select GDP, proportion of the second industry, output of coal, output of steel, throughput goods of port, infrastructure investment, railway market share and volume of freight traffic as the influence index and construct the relation among them by BP neural networks model. We also use the model to forecast the volume of freight traffic and get a satisfying effect.
出处
《北京交通大学学报（社会科学版）》
2003年第4期21-24,共4页
Journal of Beijing Jiaotong University(Social Sciences Edition)
关键词
国民经济
铁路货运量
BP神经网络模型
预测
national economy
railway freight traffic volume
BP neural networks model
forecast
