• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.175-177
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• 2014

본 연구는 부산항에서 차지하는 환적물동량의 위상을 고려하여 환적화물에 대한 정확한 예측을 위한 모델을 수립하는데 그 목적이 있다. 환적물량을 결정짓는 요소로는 부산항의 경쟁력 뿐 아니라 중국 등의 수출입 물동량 증가량과 중국항만의 경쟁력도 중요요소이며, 이들 요소들이 상호간에 영향을 주고 받음에 따라 그러한 순환적 인과관계 분석에 적합한 시스템 다이내믹스(SD) 기법을 활용하여 환적화물에 대한 예측을 시도해 보고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1094-1095
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• 2023

우리나라는 지리적 여건 상 대외무역에 대한 의존도가 높기 때문에, 해상운송에서의 물동량을 예측하여 항만시설을 개발하는 것이 매우 중요하다. 한편 우리나라 컨테이너 운송의 75%는 부산항을 통해 운송되고 있기 때문에 경기 회복을 위해서는 부산항의 경쟁력 강화가 급선무이다. [1] 물동량은 경제적 수입 뿐만 아니라, 지속가능성을 예측하는 측면에서도 가치가 있다. 본 연구에서는 물동량, 경제지수, 기후정보 등 다양한 입력변수와 LSTM 모델을 이용하여 보다 정확한 부산항 컨테이너 물동량 딥러닝 예측모델을 구현하였다.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.521-526
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• 2012

More efficient and effective volume management of trade cargo is recently requested due to FTA with foreign country. Above all, the grain is the main cargo needed in Korean food life and was appointed as the core trade cargo during FTA. This study is aimed to forecast future demands of grain volumes which are handled at Incheon port because most of the grain volumes are traded at Incheon port in Korea. System Dynamics (SD) was used for forecasting as the methodology. Also, population, yearly grain consumption per a man, GDP, GRDP, exchange rate, and BDI were used as the factors that influence grain volumes. Simulation duration was from 2000 to 2020 and real data was used from 2000 to 2007. According to the simulation, 2020's grain volumes at Incheon port were forecasted to be about 2 million tons and grain volumes handled at Incheon port were continuously reduced. In order to measure accuracy of the simulation, this study implemented MAPE analysis. And after the implementation, the simulation was decided as a much more accurate model because MAPE value was calculated to be 6.3%. This study respectively examined factors using the sensitivity analysis. As a result, in terms of the effects on grain volume in Incheon Port, the population factor is most significant and exchange rate factor is the least.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.353-359
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• 2007

Effective plan and operation managements can be established in advance if the traffic volume of container ship will be forecasted in the trend for container port's cargo volume to increase. At the viewpoint for marine traffic the number of incoming and outgoing container ship can be presumed in the long run and organised rational plan to deal the demand of marine traffic on the basis. Therefore, the paper estimated the future traffic volume of incoming and outgoing container ship for Busan, Gwangyang, and Incheon port on a forecasting data basis of container volume suggested in the national ports base plan. The trends of volume per ship on container were estimated with ARIMA models and seasonal index was computed. Thus the traffic volume of container ship in the future was estimated computing with volume per ship in 2011,2015, and 2020 respectively.

• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.425-431
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• 2008

The future cargo transportation and traffic volume on container in Gwangyang port was forecasted by using univariate time series models in this research. And the container ship traffic was produced. The constructed models all were most adapted to Winters' additive models with a trend and seasonal change. The cargo transportation on container in Gwangyang port was estimated each about 2,756 thousand TEU and 4,470 thousand TEU in 2011 and 2015 by increasing each 7.4%, 16.2% compared with 2007. The volume per ship on container was estimated each about 675TEU and 801TEU in 2011 and 2015 by increasing each 30.3%, 54.6% compared with 2007. Also, traffic volume on container incoming in Gwangyang Port was prospected each about 4,078ships and 5,921ships in 2011 and 2015.

• 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.28 no.2
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• pp.75-93
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• 2012

The steel cargoes as the core raw materials for the manufacturing industry have important roles for increasing the handling volume of the port. In particular, steel cargoes are fundamental to vitalize Port of Incheon because they have recognized as the primary key cargo items among the bulk cargoes. In this respect, the IPA(Incheon Port Authority) ambitiously developed the port complex facilities including dedicated terminals and its hinterland in northern part of Incheon. However, these complex area has suffered from low cargo handling records and has faced operational difficulties due to decreased net profits. In general, the import and export steel cargo volumes are sensitively fluctuated followed by internal and external economy index. There is a scant of research for forecasting the steel cargo volume in Incheon port which used in various economy index. To fill the research gap, the aim of this research is to predict the steel cargoes of Port of Incheon using the well established methodology i.e. System Dynamics. As a result, steel cargoes volume dealt with in Incheon port is forecasted from about 8 million tons to about 10 million tons during simulation duration (2011-2020). The Mean Absolute Percentage Error (MAPE) is measured as 0.0013 which verifies the model's accuracy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.463-465
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• 2024

본 연구는 중국 동북3성과 우리나라간의 카페리 화물 물동량 예측을 수행하여 노후 카페리선박에 대한 경제성 평가에 기초자료로 활용하고자 하며 친환경 선박으로의 대체하는데 있어 정책금융 지원에 대한 근거자료를 확보 하고자 한다.