• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.83-93
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• 2013

Land Suitability Assessment can help to evaluate whether to preserve or to develop through analysis of various land characteristics. So, the evaluation index and method are very important for making the best result. The principle objective of this dissertation is to identify effective method that can make up for the distortion of land suitability value in the forest bordering the management area. The objective area of this study is comparative flat Jeungpyeong-gun. The procedures of the study are as follows. First, implement land suitability assessment as the normal index on Guideline. Second, verify land suitability grade about the forest bordering the management area. The third, redo land suitability assessment as two alternative index on $^*$Guideline. The fourth, identify effective method between normal index and alternative index. The results of this tests show that the development suitability value is higher than preservation suitability value in the forest bordering the management area near existing development area. For that reason, this study needed to use substitution index in order to make up for the weakness. The level of land price and distance from road were main considerations. Finally, the derivative model is as follows. The derivative model confirmed the best assessment method in the forest bordering the management area near existing development area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.283-286
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• 2007

This paper proposes a genetic algorithm (GA) approach to instance selection in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in complex problem solving. Nonetheless, compared to other machine learning techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for instance selection in CBR.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1366-1372
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• 2011

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.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.357-362
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• 2012

We have compared and predicted for non-linear time series data which are real data having different variences using GRCA(1) model and neural network method. In particular, using Korea Composite Stock Price Index rate, mean square errors of prediction are obtained in genaralized random coefficient autoregressive model and neural network method. Neural network method prove to be better in short-term forecasting, however GRCA(1) model perform well in long-term forecasting.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes the hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1661-1671
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• 2016

Risk analysis is a systematic study of uncertainties and risks we encounter in business, engineering, public policy, and many other areas. Value at Risk (VaR) is one of the most widely used risk measurements in risk management. In this paper, the Korean Composite Stock Price Index data has been utilized to model the VaR employing the classical ARMA (1,1)-GARCH (1,1) models with normal, t, generalized hyperbolic, and generalized pareto distributed errors. The aim of this paper is to compare the performance of each model in estimating the VaR. The performance of models were compared in terms of the number of VaR violations and Kupiec exceedance test. The GARCH-GPD likelihood ratio unconditional test statistic has been found to have the smallest value among the models.

• Journal of Korean Society for Quality Management
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• v.38 no.1
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• pp.20-33
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• 2010

This study investigates the relationships of total quality management (TQM), organizational learning (OL) activities and business performance and examines the partial mediation effect of OL activities on business performance in Korean industrial manufacturing setting. Main target sample firms were all manufacturing companies listed in the Korea Composite Stock Price Index (KOSPI) and 206 firms participated. This study theoretically develops a conceptual model with 3 hypotheses regarding how TQM practices influence OL activities and how the OL activities partially mediate between the TQM practices and business performance. To examine these hypotheses, Structural Equation Modeling (SEM) was employed and an alternative model which includes a path between errors of leadership factor and OL construct was developed. The findings are TQM practices cannot directly influence business performance but indirectly impact business performance through OL activities. This study found that OL activities playa role as firms' critical competency to improve business performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.734-737
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• 2004

When the margin level is set relatively low, margin violation probability increases and the default probability of the futures market rises. On the other hand, if the margin level is set high, the margin violation probability decreases, but the futures market becomes less attractive to hedgers as the investor's opportunity cost increases. In this paper, we investigate whether the movement of KOSPI200(Korea Composite Stock Price Index 200) futures daily prices can be modeled with the extreme value theory. Base on this investigation, we examine the validity of the margin level set by the extreme value theory. Computational results are presented to compare the extreme value distribution and the empirical distribution of margin violation in KOSPI200. Some observations and implications drawn from the computational experiment are also discussed.

• IE interfaces
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• v.12 no.4
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• pp.487-495
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• 1999

Mobile telecommunication service is one of the most competitive and rapidly growing industries in Korea. In competitive environments, it is essential to measure and improve customer satisfaction(CS) levels. However, there are a few problems in existing methods of CS measurement. First, sacrifice such as price is not included properly. Thus, the CS is not expanded into the value concept which is important to customer's behavioral intention. Second, CS measurements are not benchmarked with other competitive companies and CS index cannot reflex it properly. AT&T experienced these problems and suggested customer value added (CVA) for CS measurement. In this study, we try to introduce the CVA concept into our mobile telecom services. CS attributes were constructed, an survey was conducted for 5 mobile telecom companies, CS survey results were presented, and the validity of CVA concept was discussed.

• Korean Journal of Mathematics
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• v.22 no.3
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.