• Korea Trade Review
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• v.48 no.2
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• pp.27-43
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• 2023

The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

• Journal of Korea Port Economic Association
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• v.23 no.4
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• pp.216-227
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• 2007

The aim of this paper is to find out the nature of causality between the two ocean freights employing the Granger method. That is because the Baltic freights tend to move very closely and seem to be behave like one time series. The Granger causality test, however, is very sensitive to the number of lags used in the analysis. This means that one has to be very careful in implementing the Granger causality test. This paper, hence, uses more rather than the lags which the Akaike Information Criterion and the Schwarz Information Criterion suggest. This study shows that BPI does not "Granger-cause" BCI and BSI, but BCI and BSI Granger-cause BPI. I also discover that BHSI does not "Granger-cause" BPI and BSI, but BPI and BSI Granger-cause BHSI. I, hence, model and estimate the ocean freight function and show that the Baltic ocean freight market is inefficient and the biased estimator of the other freight.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.47-53
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• 2019

The purpose of the study was to utilize VECM(Vector Error Correction Model) and detect causal relationships among shipping freight rates. Shipping freight rates used in this study were BDI(Baltic Dry Index), HRCI(Howe Robinson Containership Index), WS(World Scale rate) and SCFI(Shanghai Containerized Freight Index). Using weekly data published since August 2nd, 2013 to September 6th, 2019, it was discovered that BDI and WS were heavily influenced by past week's BDI and WS respectively. VECM also found that one percent increase in WS resulted in 0.022% increase in following week's HRCI data. One percent increase in HRCI affects SCFI by 0.77% on the following week. This study believes that finding may help each shipping market of shipping freight rates estimates, thereby encouraging decision markers to exercise discretion and establish best interest decision.

• Journal of Ocean Engineering and Technology
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• v.9 no.2
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• pp.156-166
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• 1995

Regrading the development of offshore natural gas field near Sakhalin Island which is an ice-infested area, this study aims to estimate the dynamic ice load for construction of offshore structures operating in this region. In this paper the design ice load and dynamic responses of a slender Arctic structure upon continuous ice movement are sutdied. Crushing agter a certain elastic deformation is assumed as a primary failure mechanism at the contact zone between semi-infinite level ice edge and the face of structure. Dynamic interaction forces are calculated using a modified Korzhavin's equation and a two-dimensional ice-structure interaction model is adopted. To verify the numerical model, dynamic analysis is performed for on of the Baltic Sea channel markers whose response patterns were presiously observed.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.3
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• pp.217-230
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• 2019

In this study, a fatigue damage estimation for an ice-going vessel navigating through broken ice fields was carried out. A numerical model to simulate the interaction between ice and structure developed using the finite element method was introduced. Time series of stresses calculated by the proposed model and the corresponding fatigue analysis results are presented. The numerical model enables the long time analysis through an efficient interaction model, the application of the periodic media analysis and the convolution integral, and it allows the stress time history to be extracted directly using the finite element method. To describe the probability distribution of stress amplitudes, the 2-parameter Weibull model was applied to the calculated stress time history, and the fatigue damage was calculated using the Palmgren-Miner rule. Finally, the fatigue damage considering the ice conditions of the Baltic Sea was calculated using the proposed method and LR method, and the results were compared to each other.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.127-132
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• 2021

This paper applies a machine learning model to forecasting freight rates in dry bulk and tanker markets with wavelet decomposition and empirical mode decomposition because they can refect both information scattered in the time and frequency domain. The decomposition with wavelet is outperformed for the dry bulk market, and EMD is the more proper model in the tanker market. This result provides market players with a practical short-term forecasting method. This study contributes to expanding a variety of predictive methodologies for one of the highly volatile markets. Furthermore, the proposed model is expected to improve the quality of decision-making in spot freight trading, which is the most frequent transaction in the shipping industry.

• Asia-Pacific Journal of Business
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• v.1 no.1
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• pp.73-95
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• 2010

European integration is characterized by the development of a transnational European identity, which is considered an integral part of the process. Northeast Asia has no similar projects to address the common identity issue, although cooperation is highly valued there as well. Identity and cooperation both require interdisciplinary approaches combining social psychology, international relations theory and international economics. This article considers the problems of applying existing studies on cooperation and identity as well as the European experience (with the Baltic Sea example) to the case of Northeast Asia. Transnational identities promote cooperation beyond the limits of rationalistic game theory, if countries of the region can define their identities and interests, commit to common goals, create shared discourses and reach a balance between nationalism and internationalism. In view of proposed negotiations on the free trade area between China, Korea and Japan and ongoing discussions about a possibility of introducing a common currency (ACU) it can be crucial to consider the importance of identity building as early as possible, before regional integration meets a stumbling block of egoistic rationality that is a problem in any model of cooperation.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.3
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• pp.231-241
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• 2019

In this study, a simplified analysis method was developed to evaluate the fatigue damage of an ice-going ship under broken ice condition. The global ice load, which is essentially calculated at the design stage of the Arctic vessel, and the hull form information were used to estimate the local ice load acting on the outer-shell of the ship. The local ice load was applied to the finite element analysis model, and the Weibull parameters for the target fatigue point were derived. Finally, fatigue damage was evaluated by applying the S-N curve and the Palmgren-Miner rule. For the verification of the proposed method, numerical analyses using direct approach were performed for the same conditions. A numerical model that implements the interaction between ice and structure was introduced to verify the local ice load and the stress calculated from the proposed method. Finally, the fatigue analyses of the Baltic Sea for actual ice conditions were performed, and the results of the proposed method, the method using numerical analysis, and the LR method were compared.

• Korea Trade Review
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• v.47 no.4
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• pp.215-231
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• 2022

Analysis and forecasting of the Baltic Capsize Index (BCI) is important for managing an entity's losses and risks from the uncertainty and volatility of the fast-changing maritime transport market in the future. This study conducted volatility transition analysis through the GARCH model, using BCI which is highly related to steel raw materials. As for the data, 2,385 monthly data were used from March 1999 to March 2021. In this study, after basic statistical analysis, unit root and cointegration test, the GARCH, EGARCH, and DCC-GARCH models were used for volatility transition analysis. As the results of GARCH and EGARCH model, we confirmed that all variables had no autocorrelation between the standardized residuals for error terms and the square of residuals, that the variability of all variables at this time was likely to persist in the future, and that the variability of the time-series error term impact according to Iron ore trade (IoT). In addition, through the EGARCH model, the magnitude convenience of all variables except the Iron ore price (IOP) and Capesize bulk fleet (BCF) variables was greater than the positive value (+). As a result of analyzing the DCC-GARCH (1,1) model, partial linear combinations were confirmed over the entire period. Estimating the effect of variability transition on BCF and C5 with statistically significant linear combinations with BCI confirmed that the impact of BCF on BCI was greater than the impact of BCI itself.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.745-751
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• 2021

The International Maritime Organization(IMO) has established Emission Control Areas(ECA) in the Baltic Sea, North Sea, and sea areas in the United States since 2012, and encourages the use of clean fuels such as Natural Gas(NG). To keep pace with the increase in international demand for LNG bunkering vessels, research for the localization of key equipment for LNG bunkering must also be performed in Korea. For research and development of core bunkering equipment and systems, in this study, heat transfer analysis and structural analysis were performed by modeling the saddle, which must first be secured structurally by directly receiving the load of the hose. As a result, the suitability of the model was reviewed by analyzing the temperature distribution and stress level through the analysis results of this study.