• Journal of Korea Port Economic Association
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• v.23 no.1
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• pp.149-162
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• 2007

The purpose of this study is to forecast the marine trading volumes using multiplicative seasonal Autoregressive Integrated Moving Average(ARIMA) model. The paper proceeds by comparing the forecasting performances of the unload volumes with those of the load volumes with Box-Jenkins ARIMA model. Also, I present the predicted values based on the ARIMA model. The result shows that the trading volumes increase very slowly.

• Journal of Korea Port Economic Association
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• v.19 no.2
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• pp.55-67
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• 2003

The purpose of this study is to estimate and forecast the marine trading volumes based on the structural model. We employ GPH cointegration test since the structural model must be stationary to get the accurate predicted values. The empirical results show that our model is stationary. This paper also applies variance decompositions and impulse-response functions to the structural model composed of exchange rate, domestic industrial activity, and world business. The results indicate that while both loading and unloading volumes respond positively to the shocks in income and then decay very slowly, their responses are different to the shocks in exchange tate.

• Journal of Korea Port Economic Association
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• v.21 no.3
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• pp.61-81
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• 2005

China has increased 10 percent every year since 1978. In particular, development and growth of Chinese ports make a remarkable in that the marine and coastal transportation handles the 90 percent of export-import cargo. This growth is beginning to threaten Korea's ports which are striving to become the hub of Northeast Asia logistics. Furthermore, the hub strategy of Northeast Asia is closely related to transshipment cargo invitation. The results of documents research indicate Busan and Gwangyang ports play an important role as an intermediate stopover between China and America. The ways to achieve transshipment cargo invitation are the construction of transshipment system based on the supply chain between korea and china, the maximization of trading volumes creation, equipment of ports infrastructure, and the constructions of the rail, road, coastal transportation infrastructures.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.16-21
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• 2014

In recent, the maritime traffic has increased with an increase in international trading volumes and the growing popularity of marine leisure activities. As increasing of maritime traffic, marine accidents happened continually and there are possibilities of accidents at sea. According to the analysis of marine accidents, most accidents occurred by human error of seafarers. To reduce the accidents by human error, the various assistance system for assist seafarers have been proposed. It is required to real-time data management method for applying to real-time system, but most proposed assistance system used off-line data for analysis. In this paper, we aim to build a navigation supporting system for providing safety information to deck officer with data of AIS(Automatic Identification System) and ARPA Radar(Automatic Radar Plotting Aids Radar), and proposed a management algorithm for real-time ship information with blackboard system and verified the validity.