• 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 Korean Society of Transportation
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• v.21 no.5
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• pp.83-95
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• 2003

This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.1-14
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• 2013

Annual average daily traffic (AADT) serves the important basic data in transportation sector. Despite of its importance, AADT is estimated through permanent traffic counts (PTC) at limited locations because of constraints in budget and so on. At most of locations, AADT is estimated using short-term traffic counts (STC). Though many studies have been carried out at home and abroad in an effort to enhance the accuracy of AADT estimate, the method to simplify average STC data has been adopted because of application difficulty. A typical model for estimating AADT is an adjustment factor application model which applies the monthly or weekly adjustment factors at PTC points (or group) with similar traffic pattern. But this model has the limit in determining the PTC points (or group) with similar traffic pattern with STC. Because STC represents usually 24-hour or 48-hour data, it's difficult to forecast a 365-day traffic variation. In order to improve the accuracy of traffic volume prediction, this study used the geostatistical approach called co-kriging and according to their reports. To compare results, using 3 methods : using adjustment factor in same section(method 1), using grouping method to apply adjustment factor(method 2), cokriging model using previous year's traffic data which is in a high spatial correlation with traffic volume data as a secondary variable. This study deals with estimating AADT considering time and space so AADT estimation is more reliable comparing other research.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.47-54
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• 2004

Recently, a large reduction in domestic aviation demand had roughly shown in the range between 34% and 75% in east central and western corridor of Korea. The reasons for the drop in air traffic demand were the provisioning of several new highway serveces and the national economic difficulties. Since April 2004, moreover, the Korea Train Express(KTX) was operated between Seoul and Daegu in the first phrase of 293Km in KTX operational distance and 258Km in air route distance. The operation of KTX significantly impacted air traffic volume, particularly on the overlapped air routes with KTX routes. This study analyzed the effects on air traffic demand in accordance with the opening of KTX by applying the Stated Preference (SP) survey method, the survey conducted prior to 8 months of the KTX initiative. Also, the comparison of the decreased demand forecast by SP analysis and actual revealed traffic volume during two months service after inauguration of KTX was conducted. The Seoul-Daegu route was analysed using the 3 variables considered access and egress time, fare rate, operational frequency. The result obtained from the analysis showed that air users would be preferred only 14%. Comparatively, however, the actual revealed air passengers after the opening KTX were remained 28%, The less "decreased demand" was caused by the instability of the KTX's operation in the initial stage. Therefore, small numbers of passenger were preferable to airservices rather than high speed railroad service.

• Journal of Korean Society of Forest Science
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• v.46 no.1
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• pp.10-20
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• 1980

This experiment was carried out to investigate the effects of physico-chemical properties of soil on the growth of Chamaecyparis obtusa and to apply the results to such rational forest management as yield forecast and selection of suitable species for a given forest stand. The soil properties observed in this experiment were soil pH, exchangeable pH organic matter, total nitrogen, available $P_2O_5$, cation exchange capacity, exchangeable $H^+$, total base and base saturation. Diameter at breast height (DBH), height and volume growth of C. obtusa were observed at 78 sampling sites. Data were processed into the following series for the analysis of multivariates : inner correlation matrix, multiple correlation coefficients, regression coefficients and partial correlation coefficients. The results are summerized as follows : 1. Multiple correlation coefficients between soil properties and DBH of C. obtusa were .364 for 20-year trees, resulting less efficient for estimating the growth of C. obtusa. However, total base, soil pH and base saturation were considerable characters for better estimation. 2. More efficient multiple correlation coefficients were observed between soil properties and height growth than those between soil properties and DBH, showing .443 for 20-year trees and factors affecting the height growth were similar to those of DBH. 3. Extremely low values of multiple correlation coefficients were estimated between physico-chemical properties of soil and volume growth of C. obtusa resulting low efficient estimation. However, total base contributed highly to volume growth of C. obtusa. Accordingly the most contributable factor for estimating the growth of C. obtusa were total base, soil pH and base saturation. Consequently, these results can be effective for selecting of the reforesting site, and less effective for estimating the growth of C. obtusa.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• The Journal of Fisheries Business Administration
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• v.51 no.2
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• pp.51-69
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• 2020

The purpose of this study is to construct an outlook model that is consistent with the "Fisheries Outlook" monthly published by the Fisheries Outlook Center of the Korea Maritime Institute(KMI). In particular, it was designed as a partial equilibrium model limited to abalone items, but a model was constructed with a dynamic ecological equation model(DEEM) system taking into account biological breeding and shipping time. The results of this study are significant in that they can be used as basic data for model development of various items in the future. In this study, due to the limitation of monthly data, the market equilibrium price was calculated by using the recursive model construction method to be calculated directly as an inverse demand. A model was built in the form of a structural equation model that can explain economic causality rather than a conventional time series analysis model. The research results and implications are as follows. As a result of the estimation of the amount of young seashells planting, it was estimated that the coefficient of the amount of young seashells planting from the previous year was estimated to be 0.82 so that there was no significant difference in the amount of young seashells planting this year and last year. It is also meant to be nurtured for a long time after aquaculture license and limited aquaculture area(edge style) and implantation. The economic factor, the coefficient of price from last year was estimated at 0.47. In the case of breeding quantity, it was estimated that the longer the breeding period, the larger the coefficient of breeding quantity in the previous period. It was analyzed that the impact of shipments on the breeding volume increased. In the case of shipments, the coefficient of production price was estimated unelastically. As the period of rearing increased, the estimation coefficient decreased. Such result indicates that the expected price, which is an economic factor variable and that had less influence on the intention to shipments. In addition, the elasticity of the breeding quantity was estimated more unelastically as the breeding period increased. This is also correlated with the relative coefficient size of the expected price. The abalone supply and demand forecast model developed in this study is significant in that it reduces the prediction error than the existing model using the ecological equation modeling system and the economic causal model. However, there are limitations in establishing a system of simultaneous equations that can be linked to production and consumption between industries and items. This is left as a future research project.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.8
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• pp.444-451
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• 2016

Most research on membrane fouling models in the past are based on theoretical equations in lab-scale experiments. But these studies are barely suitable for applying on the full-scale spot where there is a sequential process such as filtration, backwash and drain. This study was conducted in submerged membrane system which being on operation auto sequentially and treating wastewater from G-water purification plant in Incheon. TMP had been designated as a fouling indicator in constant flux conditions. Total volume of inflow and SS concentration are independent variables as major operation parameters and time-series analysis and prediction of TMP were conducted. And similarity between simulated values and measured values was assessed. Final prediction model by using genetic algorithm was fully adaptable because simulated values expressed pulse-shape periodicity and increasing trend according to time at the same time. As results of twice validation, correlation coefficients between simulated and measured data were $r^2=0.721$, $r^2=0.928$, respectively. Although this study was conducted limited to data for summer season, the more amount of data, better reliability for prediction model can be obtained. If simulator for short range forecast can be developed and applied, TMP prediction technique will be a great help to energy efficient operation.

• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.905-910
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• 2012

In early 1990s, the Sea & Air Transport Cargoes (SATC) was increased annually with more than 50% rate due to the rising trade between Korea and China. However, after that, the increasing rate of the SATC was slowdown from the late 1990s, furthermore, recently it became sluggish and declined. This phenomenon is totally different compared to the skyrocketing trade volumes between two countries. In this respect, to forecast the SATC, draw out the factors for activation, and calculate the weight of priority of these factors are urgently needed. To achieve the research objectives, the ARIMA and Fuzzy-AHP were used as research methodology. The estimated volume of SATC using the data from year 2007 to 2012 on the ARIMA model, will be reached approximately 33,000 tons in year 2015. In the mean time, For drawing out and weighing the activation factors for SATC, the Fuzzy-AHP was adopted. As a result, 'Sea & Air transportation-related information system policies' is the most important factor among the principle criteria, and 'the construction of consolidation logistics center' is the most important factor among the 12 sub-principle criteria.