• Journal of Embryo Transfer
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• v.31 no.3
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• pp.267-272
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• 2016

Wholesale beef price is the critical factor for determining Korean native cattle, Hanwoo, farm's income in short-term. Wholesale beef price has seasonality due to high demand in Korean traditional holidays such as Korean thanksgiving day and lunar new year's day. Therefore, it is important to make reproduction and marketing plans for Korean Hanwoo farmers, in order to increase their farm income. However, there is no study available on changes in the expected farm income depending on reproduction and marketing schedules. This study analyzed the expected farm income per head depending on the monthly-based marketing schedules. The analysis was conducted based on the seasonality of wholesale beef price, reproduction efficiency, operating costs, relationship between carcass grade and slaughter age. The result shows that slaughter Hanwoo at the age of 29 months-old in August and January generating the highest expected farm income per head.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.31-40
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• 2015

This study proposes a mathematical model that can forecast national defense expenditures. The ongoing European debt crisis weighs heavily on markets; consequently, government spending in many countries will be constrained. However, a forecasting model to predict military spending is acutely needed for South Korea because security threats still exist and the estimation of military spending at a reasonable level is closely related to economic growth. This study establishes two models: an Auto-Regressive Moving Average model (ARIMA) based on past military expenditures and Transfer Function model with the Gross Domestic Product (GDP), exchange rate and consumer price index as input time series. The proposed models use defense spending data as of 2012 to create defense expenditure forecasts up to 2025.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1480-1491
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• 2015

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three-layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

• Journal of electromagnetic engineering and science
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• v.11 no.3
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• pp.174-182
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• 2011

The On-line Electric Vehicle (OLEV) is an electric transport system in which the vehicle's power is transferred wirelessly from power lines underneath the surface of the road. Advantages of the OLEV include reducing battery size and cost to about 20 percent of that of conventional battery-powered electric vehicles, thereby minimizing the vehicle's weight and price, as well as the cost of charging the system. In this paper, we introduce a wireless power transfer mechanism to maximize the electrical performance of the power transfer system. Power transfer capacity, power transfer efficiency, and magnitude of leakage in the electromagnetic field (EMF) are analyzed, and the optimization methodology of the design parameters is discussed.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.861-863
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• 2005

LMP based congestion management method is suggested as an effective tool, because network congestion can be handled by energy price. It is now being widely used in the North American Electricity Markets. Among them, FGR(Flow-gate rights) is considered to be appropriate for our system, as power flow through the congested line is unidirectional and congestion occurs in the known place. In the CBP market, hedging through transmission right is not necessary even though location pricing system is adopted, because there are no risks in the energy price. Rut, transmission rights should be adopted in the advanced market. Key issue when implementing FGR is how to decide transmission right issuance quantify. This paper deals with a method to decide transmission right issuance quantity by using power. Transfer Distribution Factor(PTDF).

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.303-313
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• 2018

This study considers time series models to forecast drug expenditures in national health insurance. We adopt autoregressive error model (ARE) and transfer function model (TFM) with segmented level and trends (before and after 2012) in order to reflect drug price reduction in 2012. The ARE has only a segmented deterministic term to increase the forecasting performance, while the TFM explains a causality mechanism of drug expenditure with closely related exogenous variables. The mechanism is developed by cross-correlations of drug expenditures and exogenous variables. In both models, the level change appears significant and the number of drug users and ratio of elderly patients variables are significant in the TFM. The ARE tends to produce relatively low forecasts that have been influenced by a drug price reduction; however, the TFM does relatively high forecasts that have appropriately reflected the effects of exogenous variables. The ARIMA model without the exogenous variables produce the highest forecasts.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.73-87
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• 1998

Recently the international transfer pricing became the most popular topic in accounting of the research as well as of the practice. Modern corporations have been experiencing a lot of changes in managerial control technique as their scale and scope of activities grows and the environment in which they operate changes rapidly. If there are internal transactions in a decentralized firm, the necessity of coordination among the divisions is inevitable. Transfer pricing in a decentalized company provides an excellent example of the coordinating role of information. One of the most important reason for a form to have a decentalized structure is the improved decision making at the lower level due to better access to information. International transfer pricing is not merely a problem of pricing but coordination of transfers and other collective or individual actions to derive rents from intergration. Such coordination can be achived through the performance evaluation scheme which is partly based upon transfer price.

• 한국항공운항학회:학술대회논문집
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• 2015.11a
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• pp.237-241
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• 2015

After it first opened in 2001, Incheon International Airport (IIA) has grown into a world-class airport, leaving remarkable traces, such as being the first airport to win the ASQ Airport Serivce Price for 10 consecutive years. However, ever since its birth IIA has tried to position itself as the leading hub airport of Northeast Asia. Until this day, it has not been meeting this goal, with transfer passenger numbers and transfer rates decreasing recently. This study looks at the outer environment to discover which factors affect IIA's transfer market. Through extensive research on external analysis, the study will eventually provide a counter strategy guideline for fighting back against decreasing transfer usage.

• Journal of the Korean Society for Railway
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• v.7 no.2
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• pp.155-162
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• 2004

In order to account for a price variation of apartment that places near a newly constructed subway station, a spatial hedonic model was developed to examine spacial characteristics that affect a purchasing price of an apartment using a White Estimator. In particular, the paper aims to examine various effects of subway 7 construction on an apartment price in Seoul Metropolitan Area. As explanatory variables, an apartment size, distance to a closest subway station, distance to the Central Business District (CBD) of Seoul, the number of years after building, and a lagged variable of the apartment purchasing price were used. The lagged variable plays a role of representing a spatial weighted average of previous prices of other apartments that locate within 3 km from the apartment. For a precise study, an entire sample was divided into two sets, southern area and southwestern area of Seoul, and two different spatial hedonic models were estimated. Not only before and after analysis, but also with and without analysis were conducted to compare with different effects of the spatial characteristics of two areas. The results show that before the construction of the subway 7, the prices of the apartments in the southern area were more sensitive to the apartment size, the distance to a closest subway station, the distance to the CBD, and the prices of the other apartments locating within 3km rather than those in the southwestern area. After the construction, on contrast, it is found that the apartment purchasing prices in the southwestern area are more sensitive than those in the southern area due to people's expectation regarding a new development around the subway station. In addition, the prices of the apartments locating closely with a transfer station are more likely to go up by increase in the apartment size, the distance to the station, and the prices of the other apartments within 3 km. Compared with the negative effects of the distance to the station on the prices in the other models, the positive effect of the distance to the transfer station might be caused by the characteristics of commercial area in which people are not likely to live.