基于BP神经网络与GM(1,1)组合的北京市物流需求预测模型  

Forecasting Model for Logistics Demand in Beijing Based on Combination of BP Neural Network and GM(1,1)

作　　者：李晗 吴珍珍 张雪雪 LI Han;WU Zhenzhen;ZHANG Xuexue(Beijing Wuzi University,Beijing 101149,China)

机构地区：[1]北京物资学院,北京101149

出　　处：《物流技术》2021年第1期50-55,共6页Logistics Technology

摘　　要：通过分析影响北京市物流需求的相关因素,构建北京市物流需求预测影响因素指标体系。运用BP神经网络和GM(1,1)方法,建立北京市物流需求组合预测模型,选取近20年的统计数据对未来五年的物流需求进行预测,得出物流需求总量及变化规律,并以此提出推进北京市物流业发展的有效途径,为物流系统规划提供合理依据及有效发展途径。By analyzing the relevant factors affecting the logistics demand in Beijing,this paper constructed an index system for its forecasting.Through the BP neural network and GM(1,1)method,a combination forecasting model for the logistics demand in Beijing was then established,and based on the statistical data of the city from the past 20 years,the logistics demand in the next five years was forecast,obtaining total logistics demand volume figures and the relevant pattern of change.On the basis of the foregoing,an effective path was proposed to promote the development of the logistics industry in Beijing.

关 键 词：BP神经网络 GM(1 1)模型 物流需求预测 北京 

分 类 号：F259.27[经济管理—国民经济] F224