• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1387-1395
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• 2015

Since the financial crisis of 2008, the People's Republic of China has aggressively been pursuing the internationalization of the Chinese Yuan or Renminbi. In this regard, rapidly increasing use of the Chinese Yuan in the onshore and offshore markets are important milestones. This paper analyzes relationship between the onshore and offshore Chinese Yuan spot markets. Major findings of this paper are as follows : First, there is full feedback relationship between the Onshore and Offshore Chinese Yuan Markets. Second, the difference between the yuan's offshore exchange rate and the onshore was getting tight. Third, the offshore Yuan market affects on the onshore market based on the empirical tests.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.711-719
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• 2019

At present, wind power is the fastest growing technology in the world. The domestic market depends heavily on imports for wind tower lift. so it manage through the overseas maker. The lift manufacture, establishment and maintenance utility is increasing, localization development of one wind tower lift is necessary with domestic fundamental base technique. In this paper, we will study the components necessary for the development of onshore offshore wind tower elevators, which are currently dependent on total imports, in line with the high growth of the wind market and the enlargement of the wind power generators. First of all, endless winders and cabins, which are the core components of the offshore wind tower lift, were examined for the components that affect the structural safety. Structural analysis was performed on Sheave, which is responsible for most of the lift lifting loads, and Block Stop, a safety device that prevents the cabin from falling in an emergency. The structural suitability was evaluated by comparing with the safety factor. In addition, the on-board control panel combines the control panel of the elevator and the drive motor driving the endless winder for efficient control of the offshore wind tower lift. The addition of features improves ride comfort at departure.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.63-73
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• 2016

How effectively a wind farm captures high market prices can greatly influence a wind farm's viability. This research identifies and creates an understanding of the effects that result in various capture prices (average revenue earned per unit of generation) that can be seen among different wind farms, in the current and future competitive SMP (System Marginal Price) market in South Korea. Through the use of a neural network to simulate changes in SMP caused by increased renewables, based on the Korea Institute of Energy Research's extensive wind resource database for South Korea, the variances in current and future capture prices are modelled and analyzed for both onshore and offshore wind power generation. Simulation results shows a spread in capture price of 5.5% for the year 2035 that depends on both a locations wind characteristics and the generations' correlation with other wind power generation. Wind characteristics include the generations' correlation with SMP price, diurnal profile shape, and capacity factor. The wind revenue cannibalization effect reduces the capture price obtained by wind power generation that is located close to a substantial amount of other wind power generation. In onshore locations wind characteristics can differ significantly/ Hence it is recommended that possible wind development sites have suitable diurnal profiles that effectively capture high SMP prices. Also, as increasing wind power capacity becomes installed in South Korea, it is recommended that wind power generation be located in regions far from the expected wind power generation 'hotspots' in the future. Hence, a suitable site along the east mountain ridges of South Korea is predicted to be extremely effective in attaining high SMP capture prices. Attention to these factors will increase the revenues obtained by wind power generation in a competitive electricity market.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.51-68
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• 2018

This paper compares the differences in management performance in the logistics market and analyzes the differences in business characteristics depending on the industry types. In addition, the effects of industry types and business characteristics on management performance are examined. The analysis method used is ANOVA and K-means clustering. The implication of the study are as follows. First, in the logistics market in Japan, there was a difference in management performance among the types of industry. The warehousing service type had the highest profitability and stability among all the industry types. Second, differences in business characteristics by industry types were tested. It was found that offshore cargo transportation type was more capital intensive than the other types. In addition, warehousing service type had higher business leadership and credit transaction than others. Third, industry types and clusters based on business characteristics had a significant impact on management performance through interaction effects. For the profitability variables in detail, other clusters had a significant effect between transportation types(onshore and offshore cargo) and warehousing service type. On the other hand, in stability variables, one cluster was effective in all types, which is a characteristic that lowers both capital intensity and business leadership.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.658-665
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• 2019

Among the renewable energy resources, wind power is growing rapidly in terms of technological development and market share. Recently, onshore wind farm have been affected by limitations of terrestrial space and environmental problems. Consequently, installation sites have been moved to the sea, and the development of floating offshore wind farms that are installed at deep waters with more abundant wind conditions is actively underway. In the context of maritime traffic, the optimal site of offshore wind farms is required to minimize the interference between ships and wind turbines and to reduce the probability of accidents. In this study, genetic algorithm based AIS(Automatic Indentification System) data composed of genes and chromosomes has been used. The optimal site of floating offshore wind farm was selected by using 80 genes and by evaluating the fitness of genetic algorithm. Further, the final site was selected by aggregating the seasonal optimal site. During analysis, 11 optimal site were found, and it was verified that the final site selected usng the genetic algorithm was viable from the perspective of maritime traffic.