• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.161-169
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• 2006

Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.

• Journal of the military operations research society of Korea
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• v.8 no.2
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• pp.17-30
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• 1982

This paper offers an optimal artillery deployment scheme for the defending unit when two forces are confronted at a military front line. When proposed gun sites, types and number of guns as well as targets are given, the solutions of the two models in this paper direct each (unit of) guns to a certain location. The aim of the models is to maximize the number of guns which can hit important targets. Unlike widely used target assignment models, these models are formulated using the set covering problem concept. These models do not contain probabilities and time. Thus they are simple as models, easy in implementation, and yield tractable solutions. The dynamic and probabilistic feature of battle situations is implicitly reflected on the models. The first model is for the case that enemies' approaching route is clearly predictable, while the second model is for the unpredictable approaching route case.

• Structural Engineering and Mechanics
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• v.22 no.3
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• pp.311-330
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• 2006

Standard compression tests of steel fiber reinforced concrete (SFRC) cylinders are conducted to formulate compressive stress versus compressive strain relationship of SFRC. Axial pullout tests of SFRC specimens are also conducted to explore its tensile stress strain relationship. Cover concrete spalling and reinforcement buckling models developed originally for normal reinforced concrete are modified to extend their application to SFRC. Thus obtained monotonic material models of concrete and reinforcing bars in SFRC members are combined with unloading/reloading loops used in the cyclic models of concrete and reinforcing bars in normal reinforced concrete. The resulting path-dependent cyclic material models are then incorporated in a finite-element based fiber analysis program. The applicability of these models at member level is verified by simulating cyclic lateral loading tests of SFRC columns under constant axial compression. The analysis using the proposed SFRC models yield results that are much closer to the experimental results than the analytical results obtained using the normal reinforced concrete models are.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.585-594
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• 2003

It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.21-36
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• 2008

As the great disturbance from abusing credit cards in Korea becomes stabilized, credit card companies need to interpret credit-card delinquents classification models from the viewpoint of profit. However, hit ratio which has been used as a measure of goodness of classification models just tells us how much correctly they classified rather than how much profits can be obtained as a result of using classification models. In this research, we tried to develop a new utility-based measure from the viewpoint of profit and then used this new measure to analyze two classification models(Neural Networks and Decision Tree models). We found that the hit ratio of neural model is higher than that of decision tree model, but the utility value of decision tree model is higher than that of neural model. This experiment shows the importance of utility based measure for credit-card delinquents classification models. We expect this new measure will contribute to increasing profits of credit card companies.

• Korean Management Science Review
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• v.28 no.2
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• pp.1-16
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• 2011

In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

• Korean Management Science Review
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• v.4
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• pp.60-75
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• 1987

This paper introduces the outlines of the state-of-the-art in studying FMSs using analytical queueing network models. These include Jackson networks, reversible networks and approximate models of non-product-form networks. the focus is on identifying the major features of models as they relate to the operational characteristics of FMSs. Prescriptive models concerning the optimal design and/or operational control of FMS networks are also discussed. We notice that the presentation of materials in this paper basically follows Yao and Buzacott, On Queueing Network Models of Flexible Manufacturing Systems(FMSs), invited and published on Queueing Systems, Theory and Application 1(1986). For other analytical models of FMSs, refer to Buzacott and Yao, Flexible Manufacturing Systems : A Review of Analytical Models, Management Science 32, No.7(1986).

• IE interfaces
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• v.18 no.4
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• pp.418-430
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• 2005

We establish an efficient strategy for construction and operation of data consolidation center for multi-organization in public sector. First, we introduce important concepts on data consolidation center in public sector, and draw some success factors by analyzing several foreign and domestic cases. Second, we construct all the possible logical operational models of the center and investigate the properties and feasibility of the models. Third, we suggest a virtual operational environment for the two representative models selected by feasibility criteria among the possible logical models, and compare the two models in terms of operational cost. We also utilize AHP methodology to evaluate qualitative opinions on the two models from several experts in public information systems. As a result, we find the best alternative is the case in which all infrastructure and facilities for the center are provided by government, and common essential IT operations are integrated, associated data are consolidated and the whole operational work are outsourced to specialized IT operations service providers.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.385-395
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• 2000

In the transportation literature, many useful decision making models for ship routing and ship scheduling have been studied. But the majority of these studies are on industrial carriers, bulk carriers, or tankers. It is quite recent that a few optimization models have been developed for liner fleet routing and scheduling problems. However there have been few academic studies on decision making models for the routing or scheduling problems of passenger ships in spite of their economic importance in the entire shipping industry. The purpose of this study is to develop analytic decision making models for ship routing and scheduling for the passenger ship fleet. This study gives two optimization models, one is a linear programming model and the other a goal programming model. These two models are solved easy by commercial linear programming softwares and suggest optimal ship routing plans and many other useful implications for passenger ship fleet managers.

• Korean Management Science Review
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• v.30 no.3
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• pp.55-70
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• 2013

In this study we suggested two optimization models to determine conversion weight of convertible bonds. The problem of this study is same as that of Park and Shim [1]. But this study used Value-at-Risk (VaR) for risk measurement instead of CVaR, Conditional-Value-at-Risk. In comparison with conventional Markowitz portfolio models, which use the variance of return, our models used VaR. In 1996, Basel Committee on Banking Supervision recommended VaR for portfolio risk measurement. But there are difficulties in solving optimization models including VaR. Benati and Rizzi [5] proved NP-hardness of general portfolio optimization problems including VaR. We adopted their approach. But we developed efficient algorithms with time complexity O(nlogn) or less for our models. We applied examples of our models to the convertible bond issued by a semiconductor company Hynix.