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兰州新区区域社会货运量预测及分析

Prediction and analysis of social freight volume in the Lanzhou New Area
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摘要 兰州新区作为第五个国家级新区,已逐步形成西北内陆地区向西开放辐射的枢纽。结合区域产业与交通调研结果,采用时间序列模型、计量经济线性回归模型、单位GDP货运量法以及增长率法对兰州新区社会货运量和需求进行预测,并进行综合分析得出最终预测结果。结果显示:未来兰州市全社会货运需求呈现出稳步上升趋势,预计到2035年和2045年总需求量将达到22411万t和30708万t,其中兰州新区约占兰州市总货运量的28%,而铁路运输约占总货运市场份额20%。预测分析对推动兰州新区现代物流转型发展,降低社会物流成本,打造丝绸之路经济带重要战略支点、促进河西走廊经济带与“丝绸之路”经济带协同发展、推动甘肃内陆开放型经济发展和循环经济示范区建设具有一定意义。 As the fth national level new area,Lanzhou New Area has gradually formed a hub for the northwest inland region to open up and radiate westward.This article combines the results of regional industry and transportation research,uses time series models,econometric linear regression models,unit GDP freight volume method,and growth rate method to predict the social freight volume and demand in Lanzhou New Area,and conducts comprehensive analysis to obtain the final prediction results.The results show that in the future,the demand for freight transportation in Lanzhou City will show a steady upward trend.It is expected that the total demand will reach 224.11 million tons and 307.08 million tons by 2035 and 2045,with Lanzhou New Area accounting for about 28%of the total freight transportation volume in Lanzhou City,and railway transportation accounting for about 20%of the total freight market share.Predictive analysis has profound significance in promoting the transformation and development of modern logistics in Lanzhou New Area,reducing social logistics costs,creating an important strategic support point for the Silk Road Economic Belt,promoting the coordinated development of the Hexi Corridor Economic Belt and the"Silk Road Economic Belt",and promoting the development of an open economy and the construction of a circular economy demonstration zone in Gansu Province.
作者 马瑞莹 Ma Ruiying(Lanzhou Railway Design Institute Corporation,Lanzhou 730000,China)
出处 《青海交通科技》 2023年第5期41-46,共6页 Qinghai Transportation Science and Technology
基金 自然科学基金(18JR3RA014)。
关键词 货运量预测 兰州新区 多式联运 时间序列模型 freight volume prediction Lanzhou New Area multimodal transportation time series model
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