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A statistical forecasting model applied to container throughput in a multi-port gateway system: the Barcelona-Tarragona-Valencia case

机译:统计预测模型应用于多端口网关系统中的集装箱吞吐量:Barcelona-Tarragona-Valencia案例

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摘要

This contribution investigates the container throughput flow in a multi-port gateway system: Barcelona-Tarragona-Valencia (BTV). First, the paper examines the recent dynamics of the total and transhipment flow showing a relevant shifting of traffic share from Barcelona to Valencia. A novel model based on a two-state Markov model in conjunction with a Monte Carlo experiments is implemented to estimate the predictions of annual growth in container throughput. Verification tests show how the predictions are reasonably good with error metrics similar to other methods based on time-series analysis (trend projections and ARIMA). The strength of the method relies in the statistical nature of the predictions provided (i.e., mean and data dispersion). The method is considered suitable for short-term forecasting. The practical application of the method considers separately the import/export and transhipment container throughput, revealing a different dynamics in both container flows.
机译:此贡献调查了多端口网关系统:Barcelona-Tarragona-Valencia(BTV)中的集装箱吞吐量流。首先,本文研究了总流量和转运流量的最新动态,显示了从巴塞罗那到瓦伦西亚的流量份额的相关变化。基于二态马尔可夫模型和蒙特卡洛实验的新型模型被实现以估计对集装箱吞吐量年增长的预测。验证测试表明,与基于时间序列分析的其他方法(趋势预测和ARIMA)相似,使用误差度量的预测效果如何合理。该方法的优势在于所提供的预测的统计性质(即均值和数据离散度)。该方法被认为适用于短期预测。该方法的实际应用分别考虑了进口/出口和转运集装箱的吞吐量,揭示了两种集装箱流量的不同动态。

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