节点文献
基于多种回归模型的区域物流需求预测实证分析
The Positive Analysis on Regional Logistics Demand Multiple Regression Model
【摘要】 根据淮安市清河区域历年货运量、GDP和产业结构比例以及它们之间相关关系,分别采用线性、对数和乘幂等多种回归模型,对淮安市清江浦区域的货物运输需求总量进行预测,综合分析比较不同拟合模型的预测结果,确定货物运输量。在规划目的预测和分析过程中,采用定性分析与定量预测相结合的方法,以历史数据为依据,根据国民经济发展与货物运输量之间的关系,利用多种回归模型进行综合预测与分析。
【Abstract】 According to the freight, GDP, industrial structure ratio and the correlation between them, the linearity, logarithm and multiplication were used to forecast the total quantity of cargo transportation demand in Qingjiangpu area of Huai’an city, the results of different fitting models are compared and analyzed to determine the volume of cargo traffic. Based on the historical data,this paper uses the method of qualitative analysis and quantitative forecasting to analyze and analyze the comprehensive regression model based on the relationship between national economic development and cargo transportation.
【Key words】 regression model; logistics demand forecast; E-commerce; internet+; logistics finance;
- 【文献出处】 物流科技 ,Logistics Sci-Tech , 编辑部邮箱 ,2017年10期
- 【分类号】F224;F259.27
- 【被引频次】9
- 【下载频次】668