铁路行包运量预测模型研究

铁路行包运量预测是以运输需求和内部供给为导向,综合考虑各种影响因素,对行包运量现状和发展的正确把握.探讨利用人工神经网络结合主成分分析的方法,建立铁路行包运量预测模型,解释并预测行包专列开行后铁路行包运量的增长趋势.实例分析的仿真结果表明,采用主成分分析法的广义回归神经网络模型结构简洁、预测精度高、收敛速度快,对相关铁路部门和企业的决策具有参考意义.

Study on Prediction Model for Railway Baggage and Parcel Traffic Volume

The prediction for railway baggage and parcel traffic volume, which is oriented by transportation demand and internal supply,is the accurate grasp for the current situation and development of baggage and parcel traffic after comprehensively considering the various influencing factors.The artificial neural network combined with principal component analysis is utilized to build the prediction model for railway baggage and parcel traffic volume. The increasing trend of railway baggage and parcel traffic after ...