• 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 the Korea Society of Computer and Information
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• v.28 no.5
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• pp.155-161
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• 2023

97.5% of our country's exports and 87.2% of imports are transported by sea, making ports an important component of the Korean economy. To efficiently operate these ports, it is necessary to improve the short-term prediction of port water volume through scientific research methods. Previous research has mainly focused on long-term prediction for large-scale infrastructure investment and has largely concentrated on container port water volume. In this study, short-term predictions for petroleum and liquefied gas cargo water volume were performed for Ulsan Port, one of the representative petroleum ports in Korea, and the prediction performance was confirmed using the deep learning model LSTM (Long Short Term Memory). The results of this study are expected to provide evidence for improving the efficiency of port operations by increasing the accuracy of demand predictions for petroleum and liquefied gas cargo water volume. Additionally, the possibility of using LSTM for predicting not only container port water volume but also petroleum and liquefied gas cargo water volume was confirmed, and it is expected to be applicable to future generalized studies through further research.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.91-104
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• 2020

Seosan-Daesan Port is the sixth largest port in Korea, and it promotes port infrastructure expansion, regular route development, overseas marketing, and port incentive systems for continuous growth. In addition, the port is planning to open a regular car ferry line to Weihai, China. This study aims to provide useful research data for effective decision making by analyzing the feasibility of opening the Chinese (Weihai) car ferry route of Seosan-Daesan Port. Currently, some car ferry routes that operate between Korea and China are open at Incheon Port, the Port of Pyeongtaek-Dangjin, and the Port of Gunsan. In order to estimate the volume of cargo that will be created when the car ferry route from Seosan-Daesan Port to Weihai opens, this research analyzes the domestic cargo volume from the Chungcheongnam-do region, where Seosan-Daesan Port is located, to each of the regions where the other ports are located. We estimated the volume of cargo that can be transported on the car ferry from Seosan-Daesan Port to Weihai. As a result, by 2020, about 76,000 passengers and about 50,000 tons of cargo could be created. Suggestions were made for policy strategies that would revitalize passenger numbers and secure the cargo volume of the car ferry, along with a discussion of and the port incentive system.

• Journal of Korea Port Economic Association
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• v.34 no.1
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• pp.81-98
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• 2018

Port logistics is essential for Korea's economy which heavily rely on international trade. Vast amounts of capital and time are consumed for the operation and development of ports to improve their competitiveness. Therefore, it is important to forecast cargo volume in order to establish the optimum level of construction and development plan. Itemized forecasting is necessary for appropriate port planning, since disaggregate approach is able to provides more realistic solution than aggregate forecasting. We introduce a new time series model which is Two-way Seasonality Multiplied Regressive Model (TSMR) to forecast oil cargo volume, which accounts for a large portion of total cargo volume in Korea. The TSMR model is designed to take into account the characteristics of oil cargo volume which exhibits trends with short and long-term seasonality. To verify the TSMR model, existing forecasting models are also used for a comparison reason. The results shows that the TSMR excels the existing models in terms of forecasting accuracy whereas the TSMR displays weakness in short-term forecasting. In addition, it was shown that the TSMR can be applied to other cargoes that have trends with short- and long-term seasonality through testing applicability of the TSMR.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.97-114
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• 2018

The East Asian region, an important part of Korea's imports and exports, is expected to grow further driven by the geographical, political, economic, social, and cultural complementarity. With the recent increase in imports and exports, the port trade volume between Korea and East Asian countries is also growing. However, due to various factors, such as economic size, growth rate, port infrastructure level, and geographical location of these countries, the volume of traffic with these ports is fluctuating. Despite much research on the volatility of port trade volume and changes in port network, this study tries to supplement the gap in a more detailed study of ports in Korea and East Asia since these kinds of studies are limited. The purpose of this study is to analyze the trend of distribution routes of export container cargo among ports in Korea and to present policy and practical implications of Korean trading companies, shipping companies, logistics companies, and port authorities. This study analyzes the variability of the trade volume between Korea's major ports and Daedong. Results show that Shanghai, Ningbo, Ho Chi Minh, and Haiphong were the most important factors in terms of size and volume increase. In terms of ports, the Busan port is the port responsible for trades with Yantai, Weihai, Hakata, Kobe, Ho Chi Minh, and Haiphong; Incheon port deals with Lianyungang, Tianjin, Osaka, Kobe, Ho Chi Minh, Haiphong; Gwangyang port trades with Tianjinxingang, Weihai, Yokohama, Mihn and Tanjong, and Ulsan port is strategically important for the Yantai, Lianyungang, Nagoya, Kobe, Ho Chi Minh and Portkelang ports. Therefore, the Korean government, port authorities, and shipping and logistics companies need to strengthen logistic network cooperation with these ports and actively promote investments in them.

• Journal of Korea Port Economic Association
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• v.24 no.2
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• pp.1-17
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• 2008

In this paper the cargo transportation were forecasted for the North Port in Busan through time series models. The cargo transportation were classified into three large groups; container, oil, general cargo. The seasonal indexes of existing cargo transportation were firstly calculated, and optimum models were chosen among exponential smoothing models and ARIMA models. The monthly cargo transportation were forecasted with applying the seasonal index in annual cargo transportation expected from the models. Thus, the cargo transportation in 2011 and 2015 were forecasted about 22,900 myriad ton and 24,654 myriad ton respectively. It was estimated that container cargo volume would play the role of locomotive in the increase of the future cargo transportation. On the other hand, the oil and general cargo have little influence upon it.

• 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 Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• 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.