城市地下物流系统货运需求量预测分析  

Forecast Analysis of Freight Demand Volume in the Urban Underground Logistics System

作　　者：陈一村 郭东军 陶西贵 陈志龙 张伟锋 Chen Yicun;Dong Jianjun;Tao Xigui;Chen Zhilong;Zhang Weifeng(Academy of Military Science,National Defense Engineering Research Institute of PLA,Beijing 210007,P.R.China;The Army Engineering University of PLA,Nanjing 210007,P.R.China)

机构地区：[1]军事科学院国防工程研究院,北京100086 [2]陆军工程大学,南京210007

出　　处：《地下空间与工程学报》2021年第6期1687-1694,1741,共9页Chinese Journal of Underground Space and Engineering

基　　金：国家自然科学基金(71631007,51878660)。

摘　　要：为了解决城市地下物流系统在规划设计中面临货运需求量数据缺失的难题,针对城市地下物流系统的适用性,建立了货运需求量预测模型,以优化其网络形态和性能。根据灰色关联理论、遗传算法和BP神经网络方法,提出了基于GRT-GA-BP算法的货运需求量预测模型,进而识别影响城市地下物流系统货运需求量的关键因素,并对影响货运需求量的关键要素的历史数据进行训练以预测城市地下物流系统货运需求量。以北京市某新区规划设计的城市地下物流系统货运网络为例进行了仿真计算,案例研究结果表明,通过本文提出货运需求量预测分析方法,能够为城市地下物流系统的规划设计提供数据基础,进而合理设计网络节点和通道的货运容量。In order to solve the problem of lacking freight demand data in the planning and designing of urban underground logistics system,the paper proposed a freight demand prediction model to optimize the form and performance of ULS.Based on the grey relation theory(GRT),genetic algorithm(GA)and Back Propagation(BP)neural network algorithm,the paper proposed a GRT-GA-BP algorithm to verify the key influence factors which affects the freight demand volume of ULS,and then to train the historical data of key influence factors to predict the freight demand volume.Taking a ULS network of planning and designing in Beijing new district as an example to conduct simulation calculation,the simulation results show that the proposed algorithm can provide data basis for the planning and design of urban ULS,and then rationally design the freight capacity of network nodes and channels.

关 键 词：地下物流系统 货运 灰色关联理论 需求 预测 

分 类 号：U121[交通运输工程]