• Asia pacific journal of information systems
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• v.4 no.1
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• pp.3-31
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• 1994

Potential employers considering locations for production or service facilities typically equire detailed advance knowledge of the wages they will be expected to offer for workers in various occupational categories. The State of Missouri s Department of Labor and Industrial Relations is often contacted by organizations requesting such information. The current wage rate survey approach, initiated in 1988, allows the Department to predict an appropriate wage rate for a given occupation in certain counties, adjusted for changes in the Consumer Price Index (CPI). However, both Department employees and firms have indicated that improved prediction responsiveness and accuracy are desirable. A major deficiency of the current approach is its inability to predict wages for unsurveyed counties. This paper describes a knowledge-based system (KBS), currently in the prototype testing stage, that is expected to supplement the wage rate survey in the near future.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.7-12
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• 2003

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.97-102
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• 2001

If the Seoul-Pusan high-speed rail project is able to open its revenue service in 2004, Korea will be the fifth country with an HSR system in the world. And, it will be recorded as a major milestone in the transportation history of Korea. But, Government regulated railroad fare because railroad fare increase can bring negative influences to CPI(Consumer Price Index). Consequently, Korea National Railroad cannot afford to operate railroad independently under current railroad fare system. In this paper, we studied the railroad fare system under implementation and its influences to CPI. And then we proposed that railroad fare must be decided by competition with other transportation modes and based on the demand variance by introducing YMS(Yield Management System).

• Bulletin of the Society of Naval Architects of Korea
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• v.21 no.2
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• pp.1-7
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• 1984

This paper is concerned with an optimum design study of containerships in preliminary stage by applying economic criteria. The Net Present Value Index (NPVI) and the Required Freight Rate(RFR) are used as measures of merit. Hooke & Jeeves direct search method and External Penalty Function method of Sequential Unconstrained Minimization Techniques(SUMT) are used for solving constrained nonlinear optimization problem. Sensitivity analysis is carried out to investigate the effect on the optimum solution due to change of values in some parameters such as crane capacity, load factor, oil price, ship speed and the ratio between loaded FEU and TEU.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.329-337
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• 2003

Stock market prediction is regarded as a challenging task of financial time-series prediction. There have been many studies using artificial neural networks in this area. Recently, support vector machines (SVMs) are regarded as promising methods for the prediction of financial time-series because they me a risk function consisting the empirical ewer and a regularized term which is derived from the structural risk minimization principle. In this study, I apply SVM to predicting the Korea Composite Stock Price Index (KOSPI). In addition, this study examines the feasibility of applying SVM in financial forecasting by comparing it with back-propagation neural networks and case-based reasoning. The experimental results show that SVM provides a promising alternative to stock market prediction.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.500-504
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• 2006

본 논문에서 기술하는 연구는 한국종합주가지수(KOSPI)의 장기적 변동 경향에 대한 확률적 예측 시스템을 제안한다. 제안된 방법론은 이미 단백질 상호작용 예측 시스템과 스트레스 확률 예측 시스템 등에 적용되어 유효성이 입증된 방법으로, 이미 알려진 데이터를 바탕으로 다양한 요인들의 가능한 모든 조합에 대한 경우의 수를 고려한 학습 결과에 기반하여 새로이 주어진 대상의 요인들을 분석해서 학습시 사용된 특정 군(class)에 속할지의 여부를 확률적으로 나타내준다. 이 방법론을 구현하기 위해 실제 과거 주가지수 데이터를 수집하여 CI(Combination Interrelation)행렬을 구현하였으며, 현재 진행중인 검증작업에 대해서도 기술하였다.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1494-1500
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• 2008

Life cycle of the rolling stock is normally 20 to 40 years, though there is some difference in accordance with each vehicle. Maintenance cost is over the twice of purchasing price. and also it is true that precise statics is not managed properly except for some developed countries due to the difference of maintenance method, skills. After KORAIL introduced ERP system in 2007, maintenance cost is managed by type of cars, by unit. but, afterwards it should be controlled as an index and also more precisely. it is the best pending issues to make train maintenance efficiency, to utilize accumulated indexes. I want to attribute to train maintenance efficiency by analysing what is the problems in the present maintenance method.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.21-26
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• 2001

As competition is introduced in the electricity supply industry, congestion becomes a more important issue. Congestion in a transmission network occurs due to an operating condition that causes limit violations on the transmission capacities. Congestion leads to inefficient use of the system, or causes additional costs (Congestion cost). One way to reduce this inefficiency or congestion cost is to control the transmission flow through the installation of UPFC (Unified Power Flow Controller). This paper also deals with an optimal siting of the UPFC for reducing congestion cost by using shadow prices. A performance index for an optimal siting is defined as a combination of line flow sensitivities and shadow prices. The proposed algorithm is applied to the sample system with a condition, which is concerning the quadratic cost functions. Test results show that the siting of the UPFC is optimal to minimize the congestion cost by the proposed algorithm.

• Journal of the Korean Society of Food Culture
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• v.25 no.6
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• pp.755-763
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• 2010

The purpose of this study was to select market variables that a foodservice company should consider when expanding overseas and to regional market analysis by variables. Twenty-three different variables were derived from 17 previous studies. These were: population, urbanization rate, women employed, enrollment in tertiary education, gross domestic product, value added by service, total number of mobile cellular telephone subscribers, number of internet users, total Asian highway, inward foreign direct investment, total service imports, inflation rate, international tourist arrivals, energy use by industry, growth rates of the food consumer price index, access to urban sanitation, per capita total expenditure on health, male life expectancy at birth, adult literacy rate, contributing women family workers, passenger car, and country risk assessment. The selected variables were collected as secondary data from the UN, Asian Development Bank, International Bank for Reconstruction and Development, and Michigan State University.

• Asia Marketing Journal
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• v.16 no.1
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• pp.169-193
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• 2014

The earlier studies have verified that brand values have significant impact on financial values such as stock return and stock price to justify marketing costs for brand building. Except for Mizik and Jacobson (2008), however, little research has addressed what kinds of brand components composing brand values have a significant relationship with financial values. As a follow-up research of Mizik and Jacobson (2008), this research focuses on what kinds of relationships exist between the unanticipated change of each brand asset component and stock return, one of the financial values. The authors selected six brand asset components from the Korea-Brand Power Index(K-BPI) data in which 'Top of Mind,' 'Unaided Awareness,' and 'Aided Awareness' are brand awareness measures and 'Image,' 'Purchase Intention,' and 'Preference' are brand loyalty measures. Out of those six brand components, they found that unanticipated changes of 'Top of Mind,' 'Unaided Awareness,' 'Image,' and 'Preference' have significantly positive effect on unexpected stock return change. Therefore, they conclude that these four brand asset components provide incremental information in explaining unanticipated stock return.