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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40056

Title: Using artificial neural networks to predict container flows between the major ports of Asia
Authors: Tsai, Feng-Ming;J.W. Huang
Contributors: 國立臺灣海洋大學:航運管理學系
Keywords: container flows;decision-making;artificial neural networks;ports of Asia;supply chain management
Date: 2015-12-14
Issue Date: 2017-01-12T07:49:22Z
Publisher: International Journal of Production Research
Abstract: Abstract:Container flow information is a critical issue for port operators and liners to support their strategic planning and decision-making. This study uses artificial neural networks (ANNs) to predict container flows by considering GDP, interest rates, the value of export and import trade, the numbers of export and import containers and the number of quay cranes. ANNs are developed for data mining purposes, and the developed model can simultaneously predict container flows between the major ports of Asia. The forecasting results indicate that the prediction errors are relatively small in most selected ports, and thus shipping companies can use the container flow prediction model to make decisions concerning operations. The results can be further applied to the trend analysis of container flows among the major ports of Asia, and a community analysis of the containers was conducted for the purpose of supply chain management.
Relation: pp.1-10
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40056
Appears in Collections:[航運管理學系] 期刊論文

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