A Comparison of Forecasting Methods for Ro-Ro Traffic: A Case Study in the Strait of Gibraltar

被引：10

作者：

Moscoso Lopez, Jose Antonio ^{[1
]}

Ruiz-Aguilar, J. J. ^{[1
]}

Turias, I. ^{[1
]}

Cerban, M. ^{[2
]}

Jimenez-Come, M. J. ^{[1
]}

机构：

[1] Univ Cadiz, Polytech Sch Engn Algeciras, Intelligent Modelling Syst Res Grp, Algeciras 11202, Cadiz, Spain

[2] Univ Cadiz, Fac Econ, Res Grp Transport & Innovat Econ, Cadiz 11002, Spain

来源：

PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON DEPENDABILITY AND COMPLEX SYSTEMS DEPCOS-RELCOMEX | 2014年 / 286卷

关键词：

Forecasting; Logistics planning; Decision making tool; FEEDFORWARD NETWORKS; NEURAL-NETWORKS; TRANSPORTATION; MODELS; FLOW;

D O I：

10.1007/978-3-319-07013-1_33

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The objective of this article is to predict volumes of Ro-Ro (Roll-on, Roll-off) freight in order to apply this prediction as a decision making tool in logistics planning and port organization. This tool can help to improve supply chain performance in a Ro-Ro terminal. Seasonal ARIMA (SARIMA) and Artificial Neural Networks (ANNs) were the forecasting methods used in this study. A resampling procedure was applied in order to find out the best model from a statistical point of view using multiple comparison methods. The results have been very promising (R=0.9157; d=0.9546; MSE=0.0195)

引用

页码：345 / 353

页数：9

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