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Throughput forecasting of different types of cargo in the adriatic seaport Koper

机译:adriatic海港Koper中不同类型货物的吞吐量预测

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摘要

An accurate forecasting system has manifested its role as an enabler in supply chains (SC), which makes the operation possible in a maximally synchronized manner. Its applications have gained the attention of scholars across various disciplines such as forecasting in market behavior analysis and tourism industry; material requirement planning in production; transport and logistics foresight in networks and facilities. Seaports, as specific SC members, are not an exception. Accurate forecasting is needed in almost all aspects of the ports' operation to avoid financial losses related to inappropriate investments and planning. The paper addresses the forecasting of joint demand-supply cargo throughputs in the Adriatic Seaport Koper. The research presents a new forecasting approach, namely, DFA-ARIMAX (Dynamic Factor Analysis-ARIMAX modeling). External economic indicators were screened to obtain useful information using the DFA prior to directing the dynamic factors into the ARIMAX forecasting model. The principal component regression and Monte Carlo framework were included to identify indicators that are unique to the port. Findings revealed that a forecasting system by its enriched capabilities to predict the observed throughputs could be seen as Functional Decision Support System. The benchmarking shows that proposed models outperform competitive models. Practical implications are discussed in detail.
机译:准确的预测系统表现为作为供应链(SC)的推动器的作用,这以最大同步的方式使操作成为可能。其应用在各种学科中获得了学者的注意力,如预测市场行为分析和旅游业;生产中的材料需求规划;运输和物流远见网络和设施。作为特定SC成员的海港不是例外。在港口运作的几乎所有方面都需要准确的预测,以避免与不适当的投资和规划相关的金融损失。本文介绍了亚得里亚海港科普勒联合需求供应货物吞吐量的预测。该研究提出了一种新的预测方法,即DFA-ARIMAX(动态因子分析 - ARIMAX建模)。在将动态因素指向ARIMAX预测模型之前,筛选外部经济指标以获得使用DFA的有用信息。包含主成分回归和蒙特卡罗框架以识别港口独有的指标。调查结果显示,其丰富能力预测预测观察到的吞吐量的预测系统可以视为功能决策支持系统。基准测试显示,提出的模型优于竞争模型。详细讨论了实际意义。

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