• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.1-23
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• 2013

This paper estimates and forecasts the container throughput of Busan port using the monthly data for years 1992-2011. To do this, this paper uses the several seasonal multiplicative ARIMA models. Among several ARIMA models, the seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$ is selected as the best model by AIC, SC and Hannan-Quin information criteria. According to the forecasting values of the selected seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$, the container throughput of Busan port for 2013-2020 will increase steadily annually, but there will be some volatile variations monthly due to the seasonality and other factors. Thus, to forecast the future container throughput of Busan port and to develop the Busan port efficiently, we need to use and analyze the seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.133-134
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• 2009

선박의 대형화와 함께 해운 항만 시장이 급속히 변화하는 가운데 각 항만들은 항만 경쟁력을 가지기 위해 물동량 예측과 더불어 하역료를 바탕으로 한 부두사용료 수준에 대해 검토를 시행하고 있는 실정이다. 또한 부산북항 재개발과 관련하여 일반부두 폐쇄 및 터미널의 이전이 계획되어지는 가운데, 터미널 임대료 및 물동량 배분에 관한 연구가 활발하게 이루어지고 있다. 따라서 본 논문은 컨테이너 터미널의 주변여건 변화에 따른 컨테이너화물 물동량을 추정 및 예측하고, 기존 사용료 및 부산북항의 특정 터미널을 대상으로 향후 2020년까지의 사용료를 검토하고자 한다.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.55-74
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• 2021

The role of container ports contributes greatly to international trade and national or regional economic development by supporting maritime transportation and occupies a central position in the supply chain connecting sea and land. The performance(traffic volume) of a port generally depends on geographic, economic, and operational factors etc. For the past several decades, container port volumes have grown with fluctuation. This study amis to analyze how global ports have undergone changes in terms of cargo volume by region, size and period. For the analysis, only the volumes of global top 100 ports were used. Shift-share analysis and BCG matrix analysis were employed as methodologies. According to the result of the analysis, the relative volatility of port traffic over the past 16 years as a whole was found to be limited. On the other hand, ports in China and Southeast and Southwest Asia, which are economically growing for the last decades, showed growing trends, while ports in Northeast Asia and Europe appeared to be in a stagnant or declining phase. It also shows that most of the global ports maintain limited changes in cargo volume because they are already positioned as central ports in the region. In addition, it can be seen that the global port volume has a close relationship with the change in the economic capability of the relevant region or country.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.371-376
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• 2015

Port is responsible for the important role that creates a lot of value-added export and import-intensive countries, critical infrastructure, and in the national economy. Despite being an important facility for the past, awareness of the port is insufficient; In 2000s, increasing the world container traffic volumes, China's economic development, and trade volume in the Northeast Asia to generate a lot of are changing the perception of the role and importance of the port. According to the review of the master plan and the port recognition in Korean Port, this study examines determining factors which affects the port cargo volume. The target of the study is domestic small and medium-sized container port that receives a large hinterland cargo volume, excluding the impact of the Global Hub Port like Busan and Gwangyang port. Factors that affect the multiple regression analysis result of the port cargo volume are berthing capacity, degree of activation, connection number of countries, GRDP and number of manufacturers.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.183-188
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• 2002

The forecast of a container traffic has been very important for port and development. Generally, Statistic methods, such as moving average method, exponential smoothing, and regression analysis have been much used for traffic forecasting. But, considering various factors related to the port affect the forecasting of container volume, neural network of parallel processing system can be effective to forecast container volume based on various factors. This study discusses the forecasting of volume by using the neural, network with back propagation learning algorithm. Affected factors are selected based on impact vector on neural network, and these selected factors are used to forecast container volume. The proposed the forecasting algorithm using neural network was compared to the statistic methods.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.51-58
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• 2002

The purpose of this paper is to find some implications for Korean seaports in terms of operation and development of ports, in particular for attracting more transshipment container cargoes into major Korean seaports. This was accomplished by the O-D analysis between major Korean seaports and top 20 Chinese ports.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.617-618
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• 2020

우리나라의 지리적인 여건상 대륙과 연결되지 않기 때문에 해상운송에 절대적으로 의존하고 있다. 해상운송에 있어 항만시설의 확보가 필요하며 대외무역의존도가 높은 우리나라의 경우 더욱 중요한 역할을 한다. 항만시설은 장기적인 항만수요예측을 통해 대규모 인프라투자를 결정하며 단기적인 예측은 항만운영의 효율성을 개선하고 항만의 경쟁력을 제고하는데 기여하므로 예측의 정확성을 높이기 위해 많은 노력이 필요하다. 본 논문에서는 딥러닝 모델 중에 하나인 LSTM(Long Short Term Memory)을 적용하여 우리나라 주요항만의 컨테이너 물동량 단기예측을 수행하여 선행연구들에서 주류를 이뤘던 ARIMA류의 시계열모델과 비교하여 예측성능을 평가할 것이다. 본 논문은 학문적으로 항만수요예측에 관한 새로운 예측모델을 제시하였다는 측면에서 의미가 있으며 실무적으로 항만수요예측에 대한 정확성을 개선하여 항만투자의사결정에 과학적인 근거로서 활용이 가능할 것으로 기대된다.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.171-185
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• 2022

This study conducted a comparative analysis by period and route through a variation allocation analysis with domestic container ports to analyze the change structure of container volume at Gwangyang Port. As a result of analysis of the absolute volume of container traffic at Gwangyang Port, the period and routes that showed the highest growth values by period and route were Europe, North America, Middle East, and South America in 2001-2007. It was followed by Southeast Asia, Oceania, Far East Asia, Europe, and Japan during the 2008-2012 period. Among the sections from 2018 to 2022, there are Oceania and Southwest Asia. In order to secure container shipments at Gwangyang Port in the future, it is essential to secure routes in Europe, the Americas, and Africa, and it is necessary to secure port competitiveness through improved management and service of container terminal operators

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.108-109
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• 2010

본 연구에서는 비선형예측기법으로서 그 우수성을 인정받고 있는 인공신경망모형을 사용하여 컨테이너 물동량 예측을 수행하였다. 그러나 인공신경망모형을 사용해 시계열의 예측결과를 ARIMA모형과 같이 널리 알려진 다른 전통적인 수요예측기법들과 비교 평가한 과거 연구들을 보게 되면 각기 주장하는 바와 그 결론이 상반됨을 알 수 있다. 그래서 인공신경망의 예측성과를 높이기 위한 기존의 선행연구들의 다양한 시도들을 바탕으로 국내 항만의 컨테이너물동량을 예측하고, 그를 통해 여러 모형간의 비교 검증작업을 수행하였다.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.169-187
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• 2015

Ports as central factors of the logistics industry and principal bases in industrial activities play a significant role in the development of the social economy. This paper takes the throughput data from 2000 to 2014 of 10 container ports located in China as the research object with the Gini coefficient and employs the shift-share analysis. It aims to analyze the changes in port concentration and movement of container throughputs and propose a stage of development port system in China. The results are as follows. First, the system of container ports clearly moves northward. According to the above shift-share analysis, the throughput moves from the Pearl River Delta to the other two regions. This indicates that the center of Chinese container port system moves northward. Second, container port diversification development takes a representative position in the change of container throughput space structure. According to the calculation results of Gini coefficient, diversified development gradually predominates the change of container throughput space structure.